Author's Accepted Manuscript

QoS in IEEE 802.11-based wireless networks:A contemporary review

Aqsa Malik, Junaid Qadir, Basharat Ahmad,Kok-Lim Alvin Yau, Ubaid Ullah

PII: S1084-8045(15)00089-2DOI: http://dx.doi.org/10.1016/j.jnca.2015.04.016Reference: YJNCA1387

To appear in: Journal of Network and Computer Applications

Received date: 11 November 2014Revised date: 23 February 2015Accepted date: 27 April 2015

Cite this article as: Aqsa Malik, Junaid Qadir, Basharat Ahmad, Kok-Lim AlvinYau, Ubaid Ullah, QoS in IEEE 802.11-based wireless networks: Acontemporary review, Journal of Network and Computer Applications, http://dx.doi.org/10.1016/j.jnca.2015.04.016

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QoS in IEEE 802.11-based Wireless Networks:A Contemporary Review

Aqsa Malik, Junaid Qadir, Basharat Ahmad, Kok-Lim Alvin Yau, Ubaid Ullah.

Abstract—Apart from mobile cellular networks, IEEE 802.11-based wireless local area networks (WLANs) represent themost widely deployed wireless networking technology. With themigration of critical applications onto data networks, and theemergence of multimedia applications such as digital audio/videoand multimedia games, the success of IEEE 802.11 dependscritically on its ability to provide quality of service (QoS). A lotof research has focused on equipping IEEE 802.11 WLANs withfeatures to support QoS. In this survey, we provide an overview ofthese techniques. We discuss the QoS features incorporated by theIEEE 802.11 standard at both physical (PHY) and media accesscontrol (MAC) layers, as well as other higher-layer proposals. Wealso focus on how the new architectural developments of software-defined networking (SDN) and cloud networking can be used tofacilitate QoS provisioning in IEEE 802.11-based networks. Weconclude this paper by identifying some open research issues forfuture consideration.

Index Terms—Quality of service (QoS), IEEE 802.11, wirelessnetworks.

I. INTRODUCTION

The IEEE 802.11 wireless local area networking (WLAN)standard defines one of the most widely deployed wirelesstechnologies in the world. The popularity of wireless network-ing is driven by the ubiquity of portable mobile hand-helddevices, and the convenience of untethered communications.With the increasing deployment of multimedia content onthe Internet—such as digital video, voice over IP (VoIP),videoconferencing, and multi-player networked games—alongwith the deployment of time-sensitive critical applications,there is a strong motivation to develop QoS features to meetthe more stringent performance requirements [1].

While the Internet and data networking models of theIEEE 802.11 WLAN technology, which are based on thedatagram delivery model of IP, provide simple, adaptive andfault resilient network, they are ill-suited to QoS provisioning.The underlying datagram model of IP is a best-effort service—i.e., while the network tries to deliver packet to the destinationcorrectly without any packet losses, it makes no guarantees.Multimedia applications, in particular, need stronger guaran-tees about the minimum throughput and maximum latency towork satisfactorily. An expensive solution for ensuring QoS isto overprovision. Most of the Internet QoS effort has focusedon how to get a network with less capacity meet application

Aqsa Malik, Basharat Ahmad and Ubaid Ullah are students at the Schoolof Electrical Engineering and Computer Science (SEECS) at the NationalUniversity of Sciences and Technology (NUST), Pakistan. Junaid Qadir isan Assistant Professor at the Electrical Engineering Department of SEECS,NUST. Kok-Lim Alvin Yau is an Associate Professor at the Faculty of Scienceand Technology, Sunway University, Malaysia

requirements at a lower cost. In IEEE 802.11 WLANs, theerror and interference prone nature of wireless medium—dueto fading and multipath effects [2]—makes QoS provisioningeven more challenging. The combination of best-effort routing,datagram routing, and an unreliable wireless medium, makesthe task of QoS provisioning in IEEE 802.11 WLANs verychallenging.

In this survey, we provide a focused overview of workdone to ensure QoS in the IEEE 802.11 standard. We havethe following three goals: (i) to provide a self-containedintroduction to the QoS features embedded in the IEEE802.11 standard; (ii) to provide a layer-wise description andsurvey of techniques adopted for ensuring QoS in the IEEE802.11 networks; and (iii) to survey the applications of newnetworking architectures—such as software defined networks(SDN) and cloud computing—for QoS provisioning in theIEEE 802.11-based WLANs.

Contributions of this paper: A lot of research has beenconducted on the topic of QoS [3], including numeroussurveys that have focused on the QoS problems for specificwireless networks such as wireless sensor networks (WSNs)[4], wireless mesh networks (WMNs) [5], and IEEE 802.11-based WLANs [6] [7] [8] [9]. Our work is different from theprevious work in that we provide an updated account of QoSliterature in IEEE 802.11-based wireless networks including adiscussion of recent architectural developments, such as cloudcomputing and SDN, that facilitate finer network managementcontrol, so we have reinvigorated the interest of the researchcommunity in providing high QoS in IEEE 802.11-basedwireless networks. In addition to highlighting the QoS featuresincorporated into the IEEE 802.11 networking standard, wealso highlight different QoS approaches pertaining to differentlayers of the TCP/IP model.

Organization of this paper: This survey is organized inthe following way. In Section II, we provide a broad-basedintroduction on the general area of Internet QoS. In SectionIII, we present the QoS features which are intrinsic to IEEE802.111 for the physical (PHY) and the medium access control(MAC) layers. We provide an overview of the IEEE 802.11a/b/g and higher-throughput IEEE 802.11 standards (802.11n/ac/ad) in Sections III-A and III-B. We follow this by adiscussion on MAC layer QoS features proposed in IEEE802.11 in Section III-C. Apart from the QoS features that arepart of the IEEE 802.11 standard, various work has focused

1We note here that the IEEE 802.11 standard directly addresses the PHYand MAC layers only.

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on QoS improvement including work at the network layer(discussed in Section IV), the transport layer (discussed inSection V), the application layer (discussed in Section VI)as well as cross-layer work (discussed in Section VII). Thepromise of recent architectural developments, such as cloudcomputing and SDN, in enabling QoS, along with a surveyof proposed work, is provided in Section VIII. Thereafter, wediscuss some open research issues in Section IX. Finally, weprovide concluding remarks in Section X.

To facilitate the reader, acronyms used in this paper arecollected in Table I as a convenient reference.

II. INTERNET QOS—A BROAD INTRODUCTION

There has been a lot of work on Internet QoS, the bulk ofwhich has focused on wired networks [10] [11]. While manyof the ideas developed for Internet QoS are also applicablemore broadly to wireless QoS, wireless networks do providesome unique challenges motivating the development of newmethods [12]. In this section, we provide a broad overview ofthe abundant literature on Internet QoS.

The original applications of the Internet—such as file trans-fer and email—are elastic applications which are not boundby stringent performance requirements, and therefore matchwell with the Internet’s datagram delivery model. The modernInternet world, which is full of multimedia applications, re-quires QoS guarantees that users have come to expect from thetelecommunications networking world. To support multimediaand other interactive/high performance applications, there is aneed to support QoS features through QoS provisioning thatprovides resource assurance along with service differentiation.Various techniques have been developed to facilitate QoSprovisioning, including (i) congestion control, (ii) admissioncontrol, and (iii) traffic shaping and engineering.

In the remainder of this section, we study the problemsof resource allocation and service differentiation, and willintroduce the techniques of admission control, congestioncontrol, scheduling, as well as traffic shaping and engineeringthat can be used to facilitate QoS provisioning.

A. Resource Allocation

Fundamentally, many QoS issues stem from the problemof resource allocation. A computer network is composedof various resources—such as links of varying bandwidths,routers with varying buffer sizes—that are shared by thedifferent network applications and users. Packet delays andlosses occur if the network resources cannot meet all the trafficdemands. A network that supports QoS must actively manageresource allocation to satisfy various users’ and applications’demands. Without appropriate resource allocation, networkperformance and service quality deteriorate rapidly underheavy load due to dropped packets and congestion. There aretwo main architectural approaches to resource allocation inthe Internet: Integrated Services (IntServ) and DifferentiatedServices (DiffServ). Apart from IntServ and DiffServ, otherQoS frameworks have also been proposed [13]. We, however,

TABLE IACRONYMS USED IN THIS PAPER.

Acronym Expanded Form

AMC Adaptive Modulating SchemeAPSD Automatic Power Save DeliveryARQ Automatic Repeat reQuestATM Asynchronous Transfer ModeBER Bit Error RateBPSK Binary Phase Shift KeyingCAC Call Admission ControlCAP Control Access PeriodCbWN Cloud-based Wireless NetworkCW Contention WindowDCF Distributed Coordination FunctionDFS Distributed Fair SchedulingDIFS DCF Interframe SpaceDiffServ Differentiated ServicesDSSS Direct-Sequence Spread SpectrumEDCA Enhanced Distributed Channel AccessEDCF Enhanced DCFEDD Earliest Due DateFEC Forward Error CorrectionFHSS Frequency Hopping Spread SpectrumFCFS First-Come First-ServedFIFO First In First OutHCF Hybrid Coordination FunctionHCCA HCF Controlled Channel AccessIntServ Integrated ServicesLTE Long-Term EvolutionMAC Media Access ControlMDP Markov Decision ProcessMPDU MAC Protocol Data UnitMPLS Multiprotocol Label SwitchingMIMO Multiple Input Multiple OutputNUC Network Utilization CharacteristicOMAR Opportunistic Medium Access and Adaptive RatesOSAR Opportunistic Scheduling and Auto RatePCF Point Coordination FunctionPIFS PCF Interframe SpacingPHB Per-Hop BehaviourPSTN Public Switched Telephone NetworkQAM Quadrature Amplitude ModulationQoE Quality of ExperienceQoS Quality of ServiceRTS Request To SendSDN Software Defined NetworkingSIFS Short Interframe SpacingSISO Single Input Single OutputSTA (Wireless) StationSWN Software Defined Wireless NetworkTDM Time Division MultiplexingTXOP Transmission OpportunityVoIP Voice over IPVM Virtual MemoryWFQ Weighted Fair QueuingWLAN Wireless Local Area NetworkingWRR Weighted Round RobinWSN Wireless Sensor Network

focus only on the more important QoS framework proposals,namely IntServ and DiffServ.

1) IntServ: IntServ performs per-flow resource reservationfor service differentiation. IntServ provides services on a per-flow basis where a flow is a packet stream with common sourceaddress, destination address and port number. In IntServ, apacket scheduler is used to enforce resource allocation toindividual flows while supporting prioritization. The IntServscheduler can be used to provide delay bounds. The delaybounds can be deterministic or statistical—for deterministic

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bounds, isolation or dedication of resources is required, whilestatistical bounds can be provided when statistical multiplexing[14] is used. There are two key IntServ abstractions, namelyReserved Resources and Standard Resources. In the ReservedResource abstraction, the router must know the amount of re-sources currently reserved for on-going sessions. The StandardResource abstraction includes the capacities of the links andthe router buffers, respectively. An example is Call Setup inwhich buffers are kept at the routers. These buffers ensure aspecific amount of bandwidth is allocated to the flows at eachrouter [15] [16] [17] [18].

2) DiffServ: DiffServ, on the other hand, performs per-classresource reservation for service differentiation, and makesuse of prioritization, multiple forwarding classes, and edgepolicing to categorize traffic into different classes; and thetraffic is treated according to its respective classes. The edgerouters are responsible for the complex operations in thenetwork; while the core routers perform simple and easycomputations. The packet-handling rule in DiffServ is termedas Per-Hop Behaviour (PHB). In other words, each networkdevice along a path behaves in a certain way in which aspecific group of packets have the same priority value. ThePHB rule decides whether a packet needs to be forwarded ordropped depending on the QoS-based precedence value of thepacket. However, the framework is very complex and cannotbe applied to heterogeneous networks [19] [20] [21]. DiffServhas been used for implementing QoS in various IEEE 802.11-based wireless networks such as [22] [23].

B. Service Differentiation

Service differentiation is used to support multiple serviceswith diverse requirements—such as interactive delay-sensitiveservices along with elastic delay-tolerant file transfer services[24]. The overprovisioning of network resources is not alwayspossible in radio networks, thus making service differentiationan integral component of most QoS-based solutions. In servicedifferentiation, several parameters (e.g., packet deadline) canbe modified to define how a flow should access the wirelessmedium [4]. A variety of services can be provided by the useof simple network parameters deployed in network nodes, andthese services can be classified according to a large numberof characteristics [25]. The QoS of the system is enhancedby differentiating the priority of each host and offering themdifferent levels of QoS parameters.

Service requirements are often application-specific. Forexample, certain applications are delay-sensitive (e.g., voiceconferencing which is sensitive to round-trip delay), whileothers are concerned more with average transmission rate (e.g.,bulk file transfer). Service requirements are often expressedusing metrics (i) bandwidth, (ii) delay, (iii) jitter, and (iv) lossrate. A more comprehensive, but still non-exhaustive, listingof QoS metrics is displayed in Figure 1. To accommodate theimpact of these metrics, the network must support multipleQoS strategies to support different applications [26] [11].

The bandwidth requirements of different applications aredifferent. Some applications, such as email, remote login andaudio, require less bandwidth, while video and file transfers

Fig. 1. Taxonomy of QoS metrics (adapted from [27] and [28]).

require high bandwidth. Similarly, the delay requirementsalso differ with the type of application. Some applications,such as email, are not delay-sensitive. However, interactiveapplications, such as web browsing, videoconferencing andlive streaming, have more stringent delay requirements. Thevariation in the packet arrival time within a stream of packetsis called jitter. Email, file sharing and remote login are notaffected by jitters in the network traffic; while real-time appli-cations, audio and video do. The loss of packets in the case ofaudio and video is not of significance. The other applications,as discussed previously, cannot tolerate an increased packetloss rate in transmissions [29]. In this work, we will focusmostly on the QoS parameters of delay, throughput, andguaranteed bandwidth.

C. Admission Control

One way of supporting QoS is through admission control—in which new sessions are allowed onto the network only ifsufficient resources are available to provide service to the newand existing sessions [30]. The interest in the field of admis-sion control, has been driven by the idea that regulation ofincoming traffic flows prevents network congestion, and helpsin ensuring QoS. Call Admission Control (CAC) is a trafficmanagement system employed in public switched telephonenetworks (PSTNs) [31]. The CAC scheme is easy to imple-ment because of the homogeneous environment. However, thepresent networking environment of homogeneous network isnot preserved. Hence, the admission control function is morechallenging in heterogeneous networks (e.g., joint WLANs andIP networks) [32]. A new flow request is admitted only ifthe ongoing flows are not negatively affected. The commonparameters used for admission control are peak bandwidthrequirement and the average rate [9]. Therefore, the task ofadmission control is to maximize resource utilization in the

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network, and to control the amount of traffic to achieve thepredefined performance objectives of the current flows.

Hou et al. [33] have presented a formal theory of QoSprovisioning in unreliable wireless networks, such as the IEEE802.11-based wireless networks, which subsumes a frameworkfor jointly addressing three important QoS criteria, namelydelay, delivery ratio, and channel reliability. They also proposealgorithms and policies for admission control and schedulingthat can be implemented in IEEE 802.11-based networks. Theauthors analytically develop necessary and sufficient condi-tions to satisfy these three criteria. More details of admissioncontrol techniques in the context of IEEE 802.11 standard aredescribed later in Section IV.

D. Congestion Control

Congestion control in the modern Internet is typicallyperformed using the TCP protocol [34]. Congestion in anetwork may occur if the number of packets sent to thenetwork is greater than the number of packets a networkcan handle. Congestion control refers to the techniques tocontrol the congestion level and keep the load below thecapacity. In the QoS-integrated services, the congestion controlmechanism should be different for different kinds of sources:e.g., file transfer/ email is different from real-time voice/videoapplications [35]. The QoS enabled routers provide services tocertain flows based on their requirements. Congestion controlhelps to provide priority differentiation of flows by servicingqueues in different manners (e.g., the order in which the flowsare serviced).

E. Scheduling

Scheduling is the key to share network resources fairlyamong users in a network, and it provides service guaranteesto time-critical applications. The scheduler first decides theorder of requests to be served, and then it manages thequeues of these awaiting requests. The scheduling scheme isimportant for the networks because there are two types ofapplications. One is insensitive to the performance that usersreceive from the network, and the other has a strict bound onthe performance. The scheduling can provide different servicesto the flows using parameters such as different bandwidths—by serving only a single flow at a particular interval; differentmean delays—according to the level of priority defined forthe flow; and different loss rates—by assigning more or fewerbuffers to the flows [36]. The scheduling mechanism adoptedin the IEEE 802.11 standard is explained in detail later inSection III-C.

F. Traffic Shaping and Engineering

Traffic in data networks is bursty in nature. Traffic shaping isa technique for handling the bursty nature of the traffic enteringa network through controlling and allocating appropriate levelsof network bandwidth [29]. The goal is to regulate averagetraffic rate and reduce congestion. The traffic shaping isperformed at the boundary nodes. These nodes have classifiersthat mark the flows according to their service requirements.

The mechanisms of traffic management can be classifiedin a number of ways [3]. One possible criterion is timescale [9]. In order to achieve QoS guarantees, decisions onbuffering and forwarding must be performed quickly. Trafficengineering is the process that maximizes network utilizationthrough careful distribution of network resources [3]. Most ofthe Internet backbones currently rely on label switching byadopting ‘multi protocol label switching’ (MPLS) technology.The purpose of label switching is to enhance the scope oftraffic engineering, QoS provisioning and overlay networks[37]. The traffic shaping mechanism for the IEEE 802.11standard is defined in Section III-C.

III. QOS SUPPORT IN IEEE 802.11

Standards in the IEEE 802 project target the PHY layer andthe MAC layer. While IEEE 802.3 defines the PHY and MAClayers for wired LANs; the prominent IEEE 802.11 standard,which is the focus. The first IEEE 802.11 specification waspublished in 1997, and it has undergone numerous subsequentamendments. The IEEE 802.11 working group has varioustask groups focusing on a myriad of niche concerns with anelaborated description of the IEEE 802.11 universe providedin [38]. The focus of the various task groups can be seen in[6] [8].

Providing QoS services in applications using traditionalIEEE 802.11 standards is difficult since they provide noexplicit mechanisms for service differentiation. Various pa-rameters extracted from the general traffic layout are used toensure acceptable QoS in these networks, such as goodput—which is the measure of packet arrival rate during a fixedperiod of time; load level—which indicates the usage of amedium on per time basis; and available bandwidth—whichmeasures the rate at which new flows can send traffic withoutaffecting the existing flows in the network [39] [40]. Thelegacy standards only have the basic distributed coordinationfunction (DCF) and the optional point coordination function(PCF) enhancements, such as collision avoidance and a first infirst out (FIFO) scheduler [41]. Even with the contention-freePCF, the QoS problem could not be solved. Consequently,the services provided to the users do not have optimal per-formances for various applications including audio and videoapplications during heavy network loads [42]. In Section III-D,we present the IEEE 802.11e standard, which provides MAClayer enhancements for QoS, that incorporates traffic priorityand queueing to enable service differentiation among the flows[43].

A. QoS Support in IEEE 802.11 a/b/g

The IEEE 802.11 has evolved in different eras to satisfydiffering requirements of applications [44] [45]. The IEEE802.11a standard is part of the original IEEE 802.11 standard,and it operates in the 5 GHz range with a data rate of 54Mbps while supporting the frequency hopping spread spec-trum (FHSS) and direct sequence spread spectrum (DSSS).Unfortunately, due to the use of high frequency spectrum, thetechnique of DSSS faced the problems of short transmissionrange and interference [46]. To address this problem, IEEE

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802.11b, which is also based on DSSS technology, operatesin the 2.4 GHz spectrum with a data rate of 11 Mbps. The802.11b standard is not backward compatible with the IEEE802.11a standard. The IEEE 802.11g standard—operating at2.4 GHz with a data rate upto 54 Mbps—is introduced forbackward compatibility with the IEEE 802.11a standard.

QoS limitations of IEEE 802.11a/b/g: In the DCF-basedschemes, the access to the medium is given on first comefirst served (FCFS) basis. This creates some fairness prob-lems, which can potentially result in flows being deprived oftheir fair bandwidth share. There is no proper mechanism todistinguish between the flows on priority basis in the PCF-based environments. The legacy standards of IEEE 802.11a/b/g have no standard mechanisms to ensure QoS [47] [48].Because these standards do not incorporate admission control,performance degradation occurs during heavy traffic load.

B. QoS Support in High Throughput IEEE 802.11 (802.11n/ac/ad)

To support the need of high throughput wireless networking,various IEEE 802.11 standards have been proposed in recenttime such as the 802.11n, 802.11ac, and 802.11ad standards.The IEEE 802.11n standard is based on the multiple inputmultiple output (MIMO) technology, and it offers a highdata rate of upto 600 Mbps. The IEEE 802.11ac standardaims to support an even higher data rate of 1 Gbps, whileIEEE 802.11ad standard aims at achieving a rate upto 7 Gbpsexploiting the wideband channels available in the 60 GHzband. These new standards incorporate scheduling mecha-nisms, call admission control algorithms, and PHY and MAClayer enhancements for supporting multimedia applicationswith QoS. The interested reader is referred to a comprehensivestudy of QoS support in very high throughput IEEE 802.11architectures (IEEE 802.11 n/ac/ad) presented in [49].

C. MAC layer QoS Features for IEEE 802.11

In general, the major techniques used for ensuring QoS atthe MAC layer include admission control and scheduling. Inthe IEEE 802.11 standard, the MAC layer provides the func-tionality of addressing, framing, reliability check, and accesscoordination to the wireless medium [50]. The MAC layer withQoS enhancements aims to provide the network with a muchreduced overhead, segregating frames on the priority basis,and keeping the collisions to the least possible level. Thissection describes the techniques implemented in the legacyIEEE 802.11 standard. The rest of this subsection presents adescription of the QoS-focused IEEE 802.11e standard.

The wireless systems can be configured in two differentmodes in the IEEE 802.11 architecture: (i) the ad-hoc mode,and (ii) the infrastructure mode. The infrastructure modehas multiple stations that can communicate with each otherthrough an access point (AP), where the APs have connectivitywith a wired network at the backend. While in the ad-hoc mode, the stations can communicate directly with eachother without any intervening access points or a backendwired network. The IEEE 802.11 has two medium accesscoordination functions, namely the DCF and the PCF.

TABLE IIPRIORITY LEVELS CORRESPONDING TO VARIOUS APPLICATIONS TYPES

FOR SUPPORTING PRIORITY QUEUEING IN IEEE 802.11.

Priority 802.1 D UserPriority

802.11e AccessCategory (AC)

Description

Lowest 1 AC BK Background Traffic2 AC BK Background Traffic0 AC BE Best Effort3 AC BE Best Effort4 AC VI Video5 AC VI Video6 AC VO Voice

Highest 7 AC VO Voice, Network Management

Various kinds of QoS enhancement techniques have beenproposed for the IEEE 802.11 standard [51] [52] [53], andthey are explained in the rest of this subsection.

1) Priority Queueing: This method is used to providepriority queues at the MAC layer where data packets aresegregated on the basis of priorities. Whenever a particularstation has access to the channel, it transmits the one which hasthe highest priority among the queued packets. All the stationsmust contend with each other for access to the medium.

Priority queueing is done in a way that there are eightdifferent levels of priority, and therefore eight different queuesmust be maintained. Table II shows the classification of thesepriorities queues. The highest level or the seventh level hasthe highest priority and it is assigned to the most critical ap-plications. The next two levels, i.e. levels 5 and 6, correspondto delay-sensitive video and audio applications. Levels 4 andbelow are used for regular data traffic, as well as streamingvideo. Level 0 is left for the traffic that can tolerate all thedeficiencies of the best-effort service [54].

2) Differentiated Services: The QoS enhancements can alsobe classified in the terms of the DCF-based or the PCF-basedenhancements. Figure 2 provides a taxonomy of DCF- andPCF-based enhancements [55] for both priority queueing anddifferentiated services.

We initially discuss four main techniques for deployingdifferentiated services using DCF:

• Distributed Fair Scheduling: For good performance of asystem, it is not a fair practice to retrict the services oflow-priority traffic and to provide better services to highpriority traffic. One way is to assign more bandwidthto the high priority traffic in comparison to the lowpriority traffic. Distributed fair scheduling (DFS) is atechnique used in this respect. In this technique, each flowis assigned some weight depending on its priority andthe bandwidth it gets is then proportional to this weight.This is a centralized technique in the sense that it uses acentral AP, which has the information regarding all thetraffic flows from different stations, and can thereforeassign different weights to each of these flows. Thistechnique thus differentiates among all the traffic flowsgoing through the AP [56].The DFS scheme uses the backoff mechanism of IEEE802.11 to decide the transmission order of each station.

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Fig. 2. MAC layer QoS enhancement schemes for IEEE 802.11-based wireless networks (described in Section III-C).

When the transmission starts, each station chooses arandom backoff time. This backoff interval is a functionof packet length and the priority of the flow. The stationswith low priority flows have longer backoff intervals thanthe stations with high priority flows. Using packet sizein the backoff calculation ensures fairness amongst thestations, resulting in smaller packets being sent moreoften. In the case of a station experiencing a collision,the new backoff interval is generated using the samealgorithm.

• Varying DIFS: Another solution is to vary the distributedinter-frame spacing (DIFS) duration for differentiationamong flows [25]. For example, we know that the ACKpacket in the IEEE 802.11 standard gets higher prioritythan RTS packets, due to the fact that ACK packet waitsshort inter-frame spacing (SIFS) amount of time, whileRTS packet waits DIFS amount of time, which is muchlonger. The same idea can be taken to the data frames;in which each flow’s priority is set with a different DIFSduration. To avoid collisions, a backoff time is maintainedsimilarly in these packets as well. Such technique is muchbeneficial in real-time applications, where delays have agreater significance compared to packet loss [57].

• Differentiated Maximum Frame Length: In this approach,service differentiation is achieved in a way that differentstations can transmit frames with different maximumframe sizes. The stations with high priority flows cantransmit a larger frame than the one with the lowerpriority flows. To ensure this, there are two mechanisms:either the packets that exceed the maximum frame sizeare discarded or an upper bound on the size of packetsis maintained in each station [58]. In some cases, whenthe packet size is greater than the maximum limit, thepackets are fragmented. These fragments are sent withoutany RTS in between, waiting just for the reception ofcorresponding ACKs. These mechanisms provide us withthe same data rates as those without fragmentation [57].

• Blackburst: The blackburst scheme imposes certain con-

straints on high priority flows rather than the low priorityflows which has been considered until now [59]. In thistechnique, every station gets access to the medium for afixed interval of time [60]. Once the station gets access tothe medium, it jams the medium for a certain duration.Consider a station that has higher priority than others,and it has data packets to transmit, so it senses thechannel. Once it detects the channel has been idle forPIFS amount of time, it has the potential to transmit itsframes. Hence, after waiting for a PIFS amount of time, itenters a blackburst contention period. A jamming signal,which is called blackburst, is then sent by this station tojam the channel. The length of this blackburst signal isproportional to the amount of time a particular stationmust wait before getting access to the medium. Afterthe station has transmitted its blackburst signal, it againlistens to check if any other stations are also sending ablackburst signal. The length of this blackburst signal iscompared to check whether it is longer or shorter than itsown. Subsequently, the station with the longest blackburstshows that it has been waiting for a longer amount oftime to access the channel, hence it is the next stationto access the channel. This technique is similar to howTDM shares the same medium among the different flows,and it is used in real-time traffic and synchronization [8].

We next discuss two techniques for offering differentiatedservices using PCF:

• Distributed TDM: This mechanism uses a polling methodas in the regular PCF mechanism, but time slots are alsodefined as in the TDM approach, and each of these timeslots is assigned to a specific station. Once these timeslots are assigned, each station knows when to transmit,and thus transmission of packets can be done with a verylittle involvement of the AP [57].

• Hybrid Coordination Function: Hybrid coordinationfunction (HCF) is a new coordination function proposedin IEEE 802.11e to enhance both DCF and PCF. HCFuses two methods: the first method is contention-based

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and it is known as enhanced distributed channel access(EDCA), and the second method is contention-free andit is known as HCF-controlled channel access (HCCA).HCF uses the AP as a traffic manager which is termed asthe hybrid coordinator (HC) [61], which is a centralizedcoordinator. The HC negotiates the exchange of framesand the frame handling rules given in HCF. The HC islocated within the range of AP and works both in thecontention-based and contention-free periods. The trafficis composed of wireless station (STA) “streams” or pipes,with each STA stream associated with a set of QoSparameters [62] negotiated with the AP. The AP usesa polling method to control the traffic. It sends pollingpackets to the stations. When a station is polled, it repliesto the poll in a frame that contains the response and thedata to be transmitted. In this method, the polling is basedupon the priority on which QoS has to be ensured [63].

The various techniques for service differentiation coveredin this section are summarized in Table III along with theirmain features and advantages.

3) QoS Scheduling: A priority scheduler always selectspackets from a queue with the highest priority. Such anapproach is simple to understand, but can unfortunately lead tostarvation of lower priority packets, particularly when there isa steady flow of high priority packets. There are also deadline-based and rate-based scheduling schemes.

The process of QoS scheduling in the IEEE 802.11 standardchooses packets amongst the various flows and distributesthem on to specific links depending upon the requirementsof each flow. This distribution of flows on each link has tobe done within a small time interval and should be hardware-friendly. Scheduling is designed to provide a better throughputwhile reducing transmission times—throughput and delay be-ing the key metrics quantifying better QoS. Resource reserva-tion for different traffic flows requires synchronization amongnodes to effectively monitor the changes in resource adaptation[67]. For such kind of insurances, we need to have a real-timemonitoring mechanism for the changing network environment.The scheduler is generally operating at the MAC layer of theTCP/IP model.

In [68], a cross-layer design algorithm for QoS packetscheduling has been defined which considers delay and infor-mation shared at the PHY, MAC and network layers. It helpsin high-speed data transmission through careful monitoring ofthe constant changes in the network while providing fairnessto all flows. No that, for best-effort services, the schedulingscheme treats all flows with the same priority. Several QoSscheduling techniques have been proposed [69] [70] and manyenhancements of current techniques have been discussed [71][72] [73].

In [74], a HCF-based packet scheduler is designed andimplemented with special reference to the IEEE 802.11estandard. This design caters both the constant bit rate andvariable bit rate of the QoS-sensitive traffic and providesbandwidth support and smaller delays to all network flows.The QoS scheduling provides guaranteed services taking intoconsideration the bit rate, delay, throughput, etc. The general

algorithms that ensure QoS in scheduling are: (i) strict priority;(ii) weighted fair queueing (WFQ); (iii) weighted round robin(WRR); and (iv) earliest due date (EDD).

a) Strict Priority: In this algorithm, the buffer is parti-tioned into a number of different queues, which is equal tothe number of different priority flows. The packets are thenstored in these queues by the scheduler according to their ownpriority levels. The flows in the same queue are then sentusing the FIFO scheme. The strict priority algorithm is easyto implement but it does not guarantee any bit rate and losses.Moreover, the lower priority flows may have a zero-valuedthroughput. In [75], [76], and [77], a network calculus methodis used to evaluate the performance of a switch as it provides agood model of packet exchanges, and it determines end-to-enddelay. Note that, the strict priority scheduling is implementedin Ethernet switches. A slight modification to the strict priorityalgorithm is proposed in [78], where the different flows areassigned with different parameters. The technique is importantin the per-hop behaviour of differentiated services network.

b) Weighted Fair Queueing: The same idea of assigningeach flow with a certain priority is used, however the queuesare not served on FIFO. Each flow is assigned a specific weightaccording to the QoS requirements [79]. Hence, the bit ratevaries with each flow. A certain upper bound on the buffer sizeis implemented to give all the flows a share of the bandwidth,which is unlike to what we have seen above. An interleavedWFQ scheme is implemented in [80], where a table specifiesthe queue sequence. The table is interleaved, so higher priorityflows are visited more frequently. The scheme improves onlatency and jitter which are associated with the traffic queues.In [81], the WFQ scheme that is backward compatible withthe IEEE 802.11 standard is discussed. The simulation resultsshow that the scheme can provide appropriate bandwidthdistribution even in the presence of flows that need to betransmitted at all times.

c) Weighted Round Robin: Weighted round robin is aframe-based implementation of WFQ. The flows are segre-gated similarly in separate queues with a specific weightassigned to each queue. The management can get difficult attimes with different packet sizes. A new scheduling algorithm,called the dynamic WRR is proposed in [82]. This algorithmis suitable for all traffic forms having variable and constantbit rates. The queues of traffic are assigned a dynamic weight.It helps the network in providing multimedia services evenin the presence of bursty traffic. In [83], a modified dynamicWRR scheme is proposed. This scheme guarantees the delaysin real-time traffic and provides efficient transmission of otherforms of traffic.

d) Earliest Due Date: In the normal EDD scheme forwired networks, packets of several different flows are assigneddeadlines according to which packets are served first by thepacket scheduler with the smaller deadline indicating higherpriority. Since wireless networks show varying characteristics,the deployment of EDD is not an easy task. Therefore, in[84], a channel-dependent EDD (CD-EDD) is described. Itdepends on the channel state, and the packets are queued by

8

TABLE IIICOMPARISON OF THE MAC LAYER SERVICE DIFFERENTIATION SCHEMES USING DCF IN THE IEEE 802.11 STANDARD.

MAC scheme Main features Advantages Drawbacks References

Distributed Fair Schedul-ing (DFS)

The DFS algorithm uses the backoffmechanism as a function of packetlength and the priority of the flow.

Provides fairness to all the flows; per-formance of high priority flows is in-creased.

It has a high implementation complex-ity.

[56]

Varying DIFS Flow priority is given by setting differ-ent DIFS durations. To avoid collisions,a similar backoff time is maintained.

Provides benefits to real-time applica-tions where higher delay is more sig-nificant than lower packet loss.

Low priority traffic suffers more, whenhigh priority frames are queued.

[25]

Differentiated maximumframe length

Services are differentiated by definingmaximum frame size proportionately toa flow’s priority.

Reduces contention overhead andachieves good differentiation.

In noisy environments, longer packetsare more likely to be corrupted thanshorter ones, decreasing the service dif-ferentiation efficiency.

[58]

Blackburst The blackburst scheme jams the channelaccording to the amount of time it haswaited.

Minimizes delay of real-time flows; highpriority flows get maximum benefit inthe absence of low priority flows.

It requires constant access intervals forhigh-priority traffic, otherwise the per-formance degrades considerably.

[59] [8]

Enhanced DistributedCoordinated Function(EDCF)

EDCF is a contention-based channel ac-cess function of IEEE 802.11e whichcan provide differentiated service.

Provides better service differentiationusing priority queues.

When load increases, the network satu-rates and throughput decreases.

[64] [65]

HCF Controlled ChannelAccess (HCCA)

The hybrid controller provides trans-mission opportunities to stations withhigher priority packets.

Combines the advantages of PCF andDCF and provides Guaranteed Serviceswith a much higher probability thanEDCF.

Due to no admission control policy, itworks well only until a certain trafficload and fails when load exceeds a QoS-load upper bound.

[63] [66]

the scheduler on the basis of earliest expiry time and otherchannel parameters. The prioritized flow consequently gets thehighest transmission rate among all the flows.

4) Traffic Shaping: Traffic shaping is used to control theflows of traffic in a channel. The basic idea is to limit theamount of packets per station. A traffic controller is used tocomply the QoS requirements of each flow. Traffic shapingcan split the resources according to different requirements ofdifferent flows. The traffic shaper must adapt to the variationsin a channel. The traffic shaping mechanism has a strongimpact on the performance of a system [85]. Several trafficshaping parameters are used in the QoS model of IEEE802.11 standard: e.g., the aggregation level and the burstinglevel. Aggregation level refers to the amount of packets thatare aggregated into a single IEEE 802.11 packet. Burstinglevel refers to the amount of packets transmitted at eachtransmission opportunity [86].

D. QoS Support in IEEE 802.11e

The IEEE 802.11e standard is an important extension of theIEEE 802.11 standard focusing on QoS [87] that works withany PHY implementation. Wireless nodes equipped with IEEE802.11e features are now known as QoS stations (QSTAs)and they are associated with a QoS access point (QAP) toform a QoS basic service set (QBSS). The main feature of theIEEE 802.11e standard is that it improves the MAC layer forQoS provisioning by providing support for: (i) segregation ofdata packets based on priority requirements; (ii) negotiationof QoS parameters through a central coordinator or AP; and(iii) admission control.

The IEEE 802.11e standard introduces a contention-basedMAC layer scheme called enhanced DCF (EDCF) and apolling-based scheme called HCF controlled channel access(HCCA). Both these schemes are useful for QoS provisioning

to support delay-sensitive voice and video applications [88],and they are described next.

1) Enhanced DCF (EDCF): In the DCF configuration, acontention window is set after a frame is transmitted. Thisis done to avoid any collisions. The window defines thecontention time of various stations who contend with eachother for access to channel. However, each of the stationscannot seize the channel immediately, rather the MAC protocoluses a randomly chosen time period for each station after thatchannel has undergone transmission [89].

EDCF uses this contention window to differentiate betweenhigh priority and low priority services [64]. The central coor-dinator assigns a contention window of shorter length to thestations with higher priority that helps them to transmit beforethe lower priority ones [90] [65]. To differentiate further, inter-frame spacing (IFS) can be varied according to different trafficcategories. Instead of using a DIFS as for the DCF traffic, anew inter-frame spacing called arbitration inter-frame spacing(AIFS) is used. The AIFS used for traffic has a duration ofa few time slots longer than the DIFS duration. Therefore, atraffic category having smaller AIFS gets higher priority [91].

2) HCF Controlled Channel Access: The HCF controlledchannel access (HCCA) is IEEE 802.11e specific, and it makesuse of a Hybrid Coordinator (HC) to manage the bandwidthallocation of wireless medium [92]. The HC can obtain atransmission opportunity (TXOP) and initiate data deliveriesto provide transmission opportunities to a station with a higherpriority without any backoff; that is to say, the HC can accessthe channels after a PIFS amount of time rather than a DIFSamount of time as for the other stations [87]. As PIFS issmaller than DIFS and AIFS, the HC has a priority over theDCF traffic, and also over the ECF traffic that uses AIFS.

9

3) Control Access Period (CAP): The CAP in HCCA isa period when access to the wireless medium is controlled[41]. During this time, the HC, or the AP, gives the right ofusing the medium to a device. The AP can gain access tothe medium before any other stations, and can then providethe transmission opportunity to any station. This guaranteesdata transfer from a station irrespective of the congestion levelin the channel [93]. The AP can schedule such transmissionopportunities for each of the stations, and can provide theparameters needed for QoS provisioning [39].

a) CAP in the Contention Period: A CAP in the con-tention period is used to regulate access to the medium toguarantee various QoS parameters [94]. However, in thismethod, the AP is not the controller (or the sole decisionmaker) [95]. This is because any stations having the DCFtraffic, or any EDCA traffic, can interfere with the schedulingperformed at the AP, so this can delay the already scheduleddata transfer at a particular station. Moreover, CAPs may usean RTS to prevent other devices while contending for themedium [41]. This causes a marginal overhead [96].

b) CAP in the Contention Free Period: The contentionfree period (CFP) is the most efficient way to use the channel,and it allows the AP to have a fine control of the medium [97].During this period, the AP has full command of the medium,so the stations do not contend for the access to the medium[98]. The scheduling of the traffic, and the provision of QoSguarantee to the stations, is handled by the AP itself. TheAP can set multiple CAPs following each other and uses thesmallest possible time intervals to separate every CAP [96].

4) Other IEEE 802.11e QoS features: We now outline someother important features of the IEEE 802.11e standard. TheTXOP parameter defines a time limit for the utilization ofradio resources at the stations [87]. The automatic power savedelivery (APSD) mechanism is used by the AP to delivermultiple frames within a service period. Thereby, APs canenter sleep period until the next service period to conserveenergy [99]. The APSD mechanism has scheduled APSD andunscheduled APSD, both of which lead to power saving ascompared to the legacy IEEE 802.11. The IEEE 802.11estandard also supports block ACKs for the acknowledgment ofmultiple MAC protocol data units (MPDUs) in a single blockacknowledgment frame resulting in reduced overhead [100].

The NoAck is another enhancement that indicates the lossof a packet, so retransmission can be ensured quickly to reducedelay [101]. Direct link setup is another supported feature thatallows direct station-to-station transfer within a service set.

IV. NETWORK LAYER QOS SOLUTIONS FOR IEEE 802.11The bulk of research investigating QoS solutions for the

network layer of IEEE 802.11 networks has focused onadmission control and QoS routing. These two important facetsof network layer QoS solutions are discussed next in separatesubsections.

A. Admission ControlAlthough the enhancements explained at the MAC layer

provides service differentiation among different traffic flows,

it can ensure QoS only when network load is reasonable. Ifthe load increases beyond a certain limit, the QoS guaranteesare not ensured even to high priority traffic [102] [103].This is where the admission control mechanism helps inpreventing the network from becoming congested, by allowingor disallowing flows depending on whether the conditions arefavorable to meet QoS requirements. More specifically, thepurpose of admission control is to limit the amount of newlyadmitted traffic such that the QoS performance of existingflows is not degraded [32]. Admission control is a key compo-nent to adapt to the traffic variations according to the changingenvironment of IEEE 802.11-based wireless networks [104].In [105], Hanzo et al. has presented a very comprehensivesurvey on different admission control schemes available inthe literature. Admission control can be categorized into threedifferent methodologies [106].

1) Measurement-based Admission Control: In this scheme,the decisions are made through continuous monitoring of net-work status, such as throughput and delay. A certain thresholdis maintained according to the network status for admissionof new traffic flows. Nor et al. in [107] proposed a metriccalled network utilization characteristic (NUC) as a meansfor admission of traffic flows into network. NUC definesthe amount of channel utilized to transmit the flow over thenetwork. This scheme guarantees QoS to high priority flowsunder loaded channel environments. Another scheme presentedby Wu et al. in [108] is that each traffic class is assigned acertain portion of available resources, and these resources arethen remaining reserved for that particular class. In this regard,only the traffic with higher priority compared to the existingtraffic is admitted.

2) Model-based Admission Control: In model-basedschemes, the network status is measured based on some mod-els. The Markov chain models are quite popular in attemptsat modeling IEEE 802.11 although other approaches are alsobeing explored due to some limitations of Markovian models[109]. In [110], an analytical model is used to estimate theminimum bandwidth requirement of all flows. When a newlyadmitted flow need to be activated, the algorithm checks ifit is going to result in preservation of QoS requirements ofexisting flows.

3) Measurement-aided, Model-based Admission Control: Itis a hybrid of measurement-based and model-based schemes.The algorithm in [111] takes network measurements in aloaded environment and also the data rate requirements ofthe flow that is requesting for admission. Furthermore, achannel model is applied to predict the network conditionsand provides QoS enhancements accordingly. Another solutionis the threshold-based approach proposed in [112] in whichthe channel conditions are continuously monitored and thecontention probability is measured. When any new flowsrequest for admission, the admission control checks for thecompeting flows. The absolute bandwidth and the expecteddelay of the new flow are measured. If this satisfies thethreshold conditions, then this flow is admitted.

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B. QoS Routing Schemes

QoS routing is an essential part of the overall QoS archi-tecture in the IEEE 802.11 standard. QoS routing allows thenetwork to compute a path that supports the QoS objectives ofvarious flows under the constraints of wireless medium. Thechosen path may or may not be the shortest path, but it meetsa particular service category objectives [113] [114].

There are various metrics that can be used for measuringQoS routing performance. We describe an example work foreach metric. The metrics proposed for QoS-based routingin the literature are: (i) minimum throughput, or capacity,required in bits per second [115]; ii) maximum tolerable delayin seconds [116]; iii) maximum tolerable packet loss ratio(PLR) [117], and iv) maximum tolerable jitter [118] [119]. Inaddition to these generic metrics, there are also other metricsspecific to various layers of TCP/IP model. For example, atthe network layer, achievable throughput or residual capacity[115], end-to-end delay [120] [116], node buffer space [121],and route lifetime [122] are important metrics; at the link (orMAC) layer, link reliability [123], and link stability [122] areimportant performance metrics; finally, signal-to-interferenceratio (SIR) [124], bit error rate (BER) [125], and node’sresidual energy [126] are important performance metrics at thePHY layer. A comprehensive summary of QoS-based routingmetrics is provided in a survey paper [27].

Many QoS routing works have been proposed in literature.For instance, Matos et al. proposed that routing decisions ofvoice, video, and data be computed in a decentralized fashionat intermediate nodes in wireless multi-service networks suchthat the overall network performance is optimized per thedesired QoS [127]. There are a number of frameworks thatcan be used for QoS-based routing. We describe two suchframeworks.

1) Measurement-based QoS Routing: In [128], a frame-work is provided to achieve fairness among different priorityflows. The basic concept is to allow the high priority traf-fic to help the low priority traffic by sharing their unusedbandwidth. This scheme can considerably improve the systemperformance and it can shorten the delays when the trafficload is very high. The QoS-supporting algorithm presented in[129] helps applications to find routes that satisfy their serviceneeds, or a feedback is provided in case of non-availability ofthese resources. Thus, a protocol that is QoS-aware and alsohas admission control and feedback mechanism is proposed.Another resource reservation algorithm is proposed by Xuein [130] in which bandwidth and delay are measured veryaccurately using a MAC protocol with collision detection.These calculations are then used by the algorithm to makedecision in admission and reservation of resources.

2) Ticket-based Probing Algorithm: This algorithm usestickets to limit the number of paths observed. When anysource wants to get a QoS satisfying path to any destination,it sends probe messages along with a ticket. The number oftickets is equivalent to the number of paths searched. When thedestination receives this probe message, the path from sourceto destination is set [116].

V. TRANSPORT LAYER QOS SOLUTIONS FOR IEEE 802.11

The classical version of TCP protocol performs rate controlbased on its assumption that packet losses occur solely dueto network congestion. This assumption does not hold truefor wireless networks where channel noise and interferencecan be another significant cause of packet loss. With suchan assumption, TCP performs poorly in terms of end-to-endQoS since it may reduce the sending rate even in uncongestednetworks under the mistaken assumption that packet losses areonly caused by network congestion.

The problem of suboptimal performance of TCP in wirelessnetworks has been known for long and much effort has focusedon improving TCP’s performance [131] [132]. Most of theexisting work in the IEEE 802.11 standard is focused on theQoS requirements of multimedia applications, such as VoIP[133], and data traffic, such as web, email, media downloads,etc. But with growing demand of wireless networks, time-critical applications with voice and video do place significantQoS requirements on wireless medium. To upgrade QoS atthe transport layer, we can adopt several techniques takinginto account the delay and loss as the basic parameters. Withthe main focus on congestion control and error control, severaltechniques are discussed below.

A. Congestion Control

The bursty nature of the wireless media and path losscauses the degradation of services to applications that requirehigh video quality. This degradation is caused by networkcongestion. This is why TCP congestion control is essentialto minimize packet loss and reduce delay. Rate control is acongestion mechanism which reduces network congestion bycomparing the required bandwidth for video with the availablebandwidth [134]. Multiple standards of rate-adaptive videoencodings [135] exist for different applications, such as H.261and H.263 for video conferencing [136] [137], as well asMPEG-1 and MPEG-2 for real-time transmission [138] [139].The main purpose of a rate-adaptive encoding scheme isto enhance the video quality under a certain encoding rate.Rate control and rate shaping [138] are the algorithms forcongestion control in the IEEE 802.11 standard.

1) Rate Control: It is very important for an end-to-endprotocol to accurately estimate the appropriate sending rate fornetwork transfer since an infeasibly high sending rate can re-sult in packet losses and retransmissions. TCP retransmissionsthat result from packet losses may lead to unacceptably longdelay for QoS-aware multimedia delivery over the wirelesschannels. Rate control subsumes flow control and congestioncontrol which adjust sending rates to ensure that the sender’srate does not overwhelm the receiver and the network, respec-tively.

Two types of congestion control are in wide practice:window-based [140] and rate-based [141]. The window-basedapproach analyzes the available network bandwidth by grad-ually increasing the size of congestion window. When con-gestion is detected (through the detection of packet loss), theprotocol decreases the window size by a large amount. Theabrupt decrease in the window size in response to congestion

11

is necessary to prevent network failure. Window-based con-trol performs retransmissions which result in extensive delay,which is intolerable in case of real-time video transmission.The rate-based control approach sends at a rate based on anestimated available network bandwidth. If the estimated band-width is accurate, then network congestion can be avoided. Therate-based control approach is usually used for transportationof real-time video. Existing rate control mechanism for real-time video are source-based, receiver-based or hybrid. Theinterested reader is referred to the paper [142], and the refer-ences therein, for a description of rate-control work focusingon supporting real-time traffic in WLANs.

2) Rate Shaping: Rate shaping is the practice in which thecompressed video bit stream adjusts itself to the rate of atarget rate. We can think of a rate shaper as an interactionmedium between an encoder and the network, which matchesthe encoder’s output to the available network bandwidth. Sincerate shaper does not need any interaction with the encoder, itcan be used for any video coding scheme for both live andstored videos.

B. Error ControlThe QoS guarantees can also be made through error control.

The main role of congestion control is to avoid packet loss.However, we are unable to avoid packet loss completely in theInternet, and as a result the quality of video or other bandwidthhungry applications are affected. The error control schemes atthe transport layer are application-aware. The error recoveryschemes can be divided into two basic types:

1) Automatic Repeat Request (ARQ): The ARQ schemeuses an acknowledgement packet to indicate that a packet hasbeen received successfully. It is very efficient for high-speedwireless links because the round trip delay of the link is verysmall [145]. The ARQ scheme can be implemented at bothtransport and link layers of the OSI model [147]. The traffic issegmented into queues such that QoS guarantees are ensured.The ARQ scheme can adapt to channel errors and is moreefficient in terms of bandwidth utilization.

2) Forward Error Correction (FEC): The FEC schemeadds redundant bits to the flow which helps in recoveringthe erroneous bits. The FEC is used for the transmission ofreal-time applications which have a strict delay requirements[157] [146]. However, a drawback of FEC is the increasedoverhead even in the absence of errors in the link [158]. FEChelps in maintaining a uniform throughput and time delay inthe networks. However, the overhead increases with channelerrors because long FEC codes must be used.

C. PrioritizationThe TCP ACK prioritization method uses both the AIFS

and the minimum contention window (CWmin) parameters.The stations having smaller CWmin gets more transmissionopportunities than stations having larger value of CWmin astheir backoff counter is smaller. The AIFS parameters can beused to allow the AP to have quicker access to the wirelessmedium. Since the TCP ACKs can go freely through thebottleneck links, the performance of the system is upgraded[148].

VI. APPLICATION LAYER QOS SOLUTIONS FOR IEEE802.11

Apart from work at the lower layers, it is also possible toimplement QoS in IEEE 802.11 networks at the applicationlayer. Traditionally, the work done on application layer QoShas focused on various aspects of multimedia delivery usingtechniques such as scalable video coding [149], error cor-rection coding and rate-distortion optimization [159], sourcecoding [160], transcoding [161], adaptive transmission [161],as well as rate control [160]. We note here that most ofthe QoS work done at the application layer is cross-layeredin nature, specifically drawing upon information from, andinteracting with, other layers. We provide two brief examplesas illustration.

Chakareski et al. [159] proposed an optimization-basederror-correction coding scheme, which works at the applica-tion layer, for rate-distortion optimized multimedia streamingto wireless clients. The scheme allows the sender to computethe prioritization levels of packets to satisfy an average trans-mission rate constraint while minimizing the average end-to-end distortion

Van der Schaar et al. [149] proposed a framework for delay-constrained video streaming over IEEE 802.11 a/e WLANs.The authors considered the problem of video transmission overHCCA and developed a cross-layered optimization frameworkworking at the PHY, MAC, and application layer of the TCP/IPlayered model. In another cross-layered video streaming paper[154], Li and Van Der Schaar proposed an error protectionscheme for transmission of layered coded video to provideadaptive QoS through prioritized queuing at the network layerand limitation of retries (or retransmissions) at the link layer.The basic insight of this work is that different video layers ofvarying importance may not receive uniform processing andprotection, but may receive unequal priority depending on thechannel conditions.

The techniques for enhancements of various layers (e.g.,MAC, network, transport and application layers) are summa-rized in Table IV.

VII. CROSS-LAYER QOS SOLUTIONS FOR IEEE 802.11

While most QoS enhancement techniques are implementedat the MAC layer, wireless QoS can benefit from cross-layeredinteraction and implementation [162]. Since QoS provisioningentails various issues that span the range of the TCP/IP layeredstack, cross-layer solutions are finding increasing deployment.

This section discusses a few cross-layered solutions forimplementing QoS in wireless networks in general, and inIEEE 802.11 networks in particular. The various techniquesfor cross-layer enhancements discussed in this section aresummarized in Table V.

A. Cross-layer Features for Wireless Multimedia

With increasing multimedia traffic on the Internet and wire-less access being anticipated to become the future predominantInternet technology [163], delivering multimedia applicationswith enhanced QoS has become extremely important. Wirelesschannel information cannot be predicted easily due to deep

12

TABLE IVLAYERED OVERVIEW OF QOS TECHNIQUES IN THE IEEE 802.11-BASED WIRELESS NETWORKS.

QoS Enhancement Technique(s) Description QoS metric used Reference(s)

MAC LayerPriority Queueing Data packets are segregated based on their priorities in queues. The packets

with the highest priority are transmitted first and so on.Buffer fullness [54] [55]

Distributed Fair Scheduling Each flow is assigned bandwidth according to its priority. Backoff interval [56]Varying DIFS DIFS is varied in order to differentiate among flows. Each flow’s priority is

set by giving it a different DIFS.Time to transmit

Maximum Frame Length High priority stations can transmit larger frames comparatively. Packet length [57]Enhanced DCF Shorter contention windows are assigned to higher priority stations helping

them to transmit first.System-level data rate [90] [91]

Blackburst Contention period is used to indicate the waiting time for medium access. Normalized MAC load [8]

Network LayerAdmission Control The network is thoroughly examined and when congestion occurs, the nodes

decrease their best-effort traffic in response.Loss, Jitter [143] [102]

QoS Routing Some routing mechanisms are used under which QoS paths are determined.QoS path may or may not be similar to the shortest path.

Delay, PLR [144] [113] [114][127]

Transport LayerCongestion Control The congestion control mechanism orders the source to transmit traffic at a

rate that is not greater than the available network bandwidth.Application-level data rate, Bufferfullness

[134] [140] [141]

Error Correction Forward Error Correction and Automatic Repeat Request are used to ensurereliability.

BER, PLR [145] [146] [147]

TCP ACK Prioritization The Contention Window and AIFS are used for flow prioritization. Residual capacity, PLR [148]

Application Layer:Scalable Video Coding A cross-layered framework is proposed for delay-constrained video streaming

over IEEE 802.11 a/e WLANs. The framework works at the PHY, MAC, andapplication layers of the TCP/IP layered model.

End-to-end delay, PLR, Jitter [149]

Transcoding Video transcoding reencodes the stream to adapt the bit rate to the availableresource.

Average Service Response Ratio,Startup Latency, Cache hit ratio

[150] [151]

Application layer Error Control An application layer optimization-based error correction coding scheme forrate-distortion optimized multimedia streaming to wireless clients.

End-to-end distortion, Relativeone-way trip time (ROTT)

[152] [153]

Real-time Retry Limit Adaptation A real-time retry-limit adaptation is proposed at the link layer for video withadaptive QoS.

Buffer capacity, Delay, BER [154]

Hybrid ARQ/ FEC Multicast and unicast real-time video streaming approaches over WLANs areimplemented through a hybrid ARQ algorithm that combines FEC and ARQ.

Latency, Reliability, Energy effi-ciency

[155] [156]

fades and multipath effects, but getting information of sourcemotion using video sequence is not hard. Due to the error-prone nature of wireless medium, and the undifferentiatednature of Internet’s best-effort service model, multimediadelivery over the wireless networks is technically challenging.To improve user experience over the wireless Internet, QoSsupport can be introduced at different layers.

In [164], the authors propose a cross-layered architecture—combining application-level, transport-layer, as well as link-layer controls—for supporting multimedia delivery over wire-less Internet. These controls incorporate issues such as dy-namic estimation of network and channel; adaptive error con-trol, congestion control, and ARQ mechanisms; and prioritybased scheduling. In another work [165], a cross-layer frame-work is proposed in which the source motion is captured froma video sequence, and it consists of a packetization scheme,a cross-layer FEC-based unequal error protection scheme,and an intra coding rate selection scheme. This significantlyimproves transmission of bursty traffic and its losses over thewireless network without making the system complex.

In order to ensure QoS in real-time applications, we canbound delay instead of high spectral efficiency [166]. Forexample, we can ensure QoS for multimedia applications byanalyzing the impact of the PHY layer on the data link layer.The single input and single output (SISO) mechanism is usedwith adaptive modulating schemes at the physical layer; and

at the data link layer, we check the impact of the physicallayer on the delay bound. Physical layer is modeled using afinite-state Markov chain. The use of appropriate schedulingschemes, and the resources allocated to the users can thusensure high QoS for each user. This technique allocatesresources to real-time users in time slots in a dynamic methodusing SISO along with adaptive modulating codes.

B. Adaptive Modulating Scheme (AMC)

There are various works in literature that have proposedcombining QoS reservation and scheduling at the MAC layerwith adaptive modulation and coding (AMC) at the PHYlayer. For instance, Liu et al. [167] have proposed an hybridarchitecture combining QoS reservation and scheduling at theMAC layer with AMC at the PHY layer. With AMC, thephysical transmission parameters can adapt to the changes inthe link quality. As an example, the PHY layer can fallbackto a modulation scheme more robust to noise, such as BPSKinstead of QAM-16, in the case link quality degrades.

In [168], the authors derive an optimal policy to reducethe average amount of dropped packets of a delay-controlledwireless node. The presented framework utilizes adaptivemodulation for transmission of the optimal amount of packetsto satisfy the QoS requirements. This framework, devised asa Markov decision process (MDP), works on reducing the

13

long-term packet drop rate. In another work [169], a cross-layered approach is presented for mobile wireless networkswhich studies the impact of the PHY layer infrastructure overthe link layer QoS performance. This work considers MIMOdiversity schemes along with AMC in its PHY layer analysis,while also studying the impact of the PHY layer infrastructureon real-time multimedia QoS provisioning performance at thelink layer.

C. Wireless Scheduling

The interaction between packet scheduling and the PHYlayer is studied in [170] where the network is used efficientlyby predicting the future state of the wireless channel, as well ascontrolling the transmission power in multipath fading wirelessCDMA networks. It is based on cross-layered model in whichthe information received from PHY layer is utilized by thescheduler, and an efficient cross-layer packet scheduling isproposed which guarantees users guaranteed QoS performancein terms of delay, BER, and received signal strength.

D. Cooperative Communications

QoS can also be ensured by using cross-layered designtaking into account the PHY and networking layers using co-operative communication [171]. Cooperative communicationis first studied at PHY layer, followed by routing to ensureQoS in the network: i.e., we use an optimized link cost for thedecision making of our routing leading to better path selection.The power consumption is kept to a minimum possible value,and end-to-end reliability is achieved by reducing the errorrate. The selection of the best possible path leads to end-to-end reliability and thus the ensuring of QoS. In [175],the authors describe a novel concept named cooperative QoSrouting, which sets up a routing path that helps to satisfy user’sbandwidth requirement. The authors propose an optimizationproblem, called ‘widest cooperative routing path’(WCRP)problem, which finds a cooperative routing path with themaximum uninterrupted bandwidth and a scheduling schemeto evade interference.

E. Combining Channel Coding and Retransmissions

The transport layer ensures a reliable transmission by re-sending corrupted packets due to congestion. However, packetsmay get corrupted in wireless networks due to other reasonssuch as fading and multipath effects. The requests for repeatedtransmission for the packet in such cases would negativelyimpact the performance of the network. To cater to thisproblem, joint cross-layer techniques are used. FEC and ARQare used as error correction codes; where FEC is used in delay-sensitive applications [176], while ARQ is used for delay-tolerant applications (e.g., audio/video streaming). In most ofthe applications, FEC does not negotiate with the receiver forerror correction because of the delay-sensitive nature althoughfeedback from the receiver can be effective [172] [173]. Usinghybrid schemes corrects the errors in an adaptive mannerby using combined channel coding and retransmissions thusimproving the TCP performance. Recently, network coding

has been extensively used in wireless networks to upgrade thelimited wireless capacity. In WLANs, network coding can beapplied to packet retransmission. More than one packet can beevenly transmitted by a single retransmission at base station.In [177], the retransmission is based on network coding, andit cooperates with IEEE 802.11e EDCA. Consequently, QoSof high priority group is upgraded from the aspect of efficientloss recovery.

F. Joint Cross-layer Techniques

This subsection presents four main joint cross-layer tech-niques.

1) Joint Rate Control, Admission Control, and Scheduling:The main goal of an Internet designer is to share the resourcesefficiently. To use the scarce bandwidth in an efficient way, itis usually the case that real-time traffic co-exists with the restof the traffic. We can jointly solve rate-control, admission-control, and scheduling problems for optimized solutions. Ininfrastructure-based networks, the EDCF is providing QoSto the nodes; but in distributed multihop networks, it is notpossible due hidden terminal and interference problems. Thus,admission control puts a limit on real-time traffic that canoverwhelm the system. By collaboration with nearby nodes,the interfering best-effort traffic is cut down to reduce thecontention of real-time traffic. A scheme called SoftMACis proposed in [178] to use a control mechanism in orderto regulate real-time and best-effort traffic in a distributedmanner by coordinating with neighboring nodes. SoftMACuses admission control to make sure that real-time traffic hassufficient bandwidth along its path. It also caters for ratecontrol to avoid collisions between the real-time traffic and thebest-effort traffic. Moreover, it has a priority queueing moduleto prioritize the real-time traffic.

QoS for wireless networks can be ensured by joint solutionsworking at the PHY and network layers. Such solutions caninclude joint routing and rate allocation to ensure QoS fordifferent applications. Zhang et al. have proposed a frameworkfor cross-layer design for QoS support in multihop wirelessnetworks, and have reviewed in detail the interplay betweenjoint routing at the network layer and rate allocation at thetransport layer. In another paper [179], Zhu et al. discussan optimization of joint allocation rate and multipath routingwhich allocates rates depending upon the distortion rate andcongestion level. This paper considered the problem of rateallocation for multi-user video streaming sharing multiple het-erogeneous access networks. The problem was formulated asa convex optimization problem and distributed approximationof the optimization was proposed.

2) Joint Power Control, Scheduling, and Routing: Variousworks in literature have demonstrated the deficiencies of thetraditional siloed approach of independently performed powercontrol, scheduling, and routing in wireless networking [180][162]. It is worth highlighting the strongly coupled nature ofthe these problems by noting that a change in power allocation,or the schedules on a given link, can impact flows that donot utilize the modified link. Due to the strong coupling

14

TABLE VOVERVIEW OF CROSS-LAYER ENHANCEMENT TECHNIQUES IN THE IEEE 802.11-BASED WIRELESS NETWORKS.

Feature(s) Description References

Wireless Multimedia SISO is used with adaptive modulation schemes at the PHY layer; and the impact on delay bound ismeasured at the data link layer.

[166]

Adaptive Modulating Scheme The node with the highest priority is assigned resources first, and each type of connection adopts AMCat the PHY layer.

[169]

Wireless Scheduling The information received from the PHY layer is utilized, and an efficient cross-layer packet schedulingapproach is proposed which guarantees QoS parameters like delay, BER and received signal strength.

[170]

Cooperative Communications QoS is ensured by using cross-layer design taking into account the PHY and network layers usingcooperative communication.

[171]

Channel Coding and Retransmissions The use of hybrid schemes corrects the errors in an adaptive manner by using a combined scheme ofchannel coding and retransmissions, thus improving the TCP performance.

[172] [173]

Dynamic Priority Functions Defined for new nodes which are updated dynamically. AMC and MIMO are used accordingly for QoSprovisioning.

[169]

Cross-layer Perceptual ARQ A cross-layer priority-based ARQ algorithm for H.264 video streaming in IEEE 802.11 wireless networks. [174]

between the network, MAC, and PHY layers, the powercontrol, scheduling, and routing problems are best addressedjointly.

With joint scheduling and power control, a network can gen-erally achieve higher throughput and lower delay in a network[180], although for some unbalanced topologies, schedulingalone cannot satisfy bandwidth requirements and rerouting isalso needed to send some packets through alternative routesand thereby release congestion. The routes are then selectedaccording to the joint metric of energy consumed and trafficaccumulated, with priority given to nodes with longer queuelength. A similar approach is presented in [181] which aimsto minimize the total average transmission power in a wirelessmulti-hop network through optimal link scheduling and powercontrol. This work, however, requires tight time synchroniza-tion between transmitters, and quasi-static channel conditionsthat remain constant over several time slots, thus limiting theapplicability of this work to interconnecting stationary nodes.

3) Joint Scheduling and Rate Optimization for Opportunis-tic Transmission: In order to utilize the scarce resources of thewireless networks, opportunistic transmission takes advantageof the varying nature of the channel and improves throughputof the network. Two approaches are used in this regard:the first one uses the time diversity of an individual linkby changing the transmission rate according to the channelconditions [182] [183], while the second one considers multi-user diversity and jointly considers the time and spatial het-erogeneity of a channel. Wang et al. [184] have proposed aMAC solution named ‘opportunistic scheduling and auto rate’(OSAR) which jointly considers rate adaptation and multi-user diversity. OSAR protocols exploits the channel variationsby automatically adjusting the sending rate to best matchthe channel conditions. In a followup work, Wang et al.have proposed another solution ‘opportunistic medium accessand adaptive rates’ (OMAR) [185], which aims at efficientutilization of the shared medium in IEEE 802.11-based ad-hocnetworks through joint consideration of multi-user diversity,distributed scheduling, and adaptivity. OMAR uses a clusteringframework in which a node with a predefined number of links

can function as the clusterhead to locally coordinate multiusercommunication. The clusterhead is responsible for initiatingmedium access, while the cluster embers make medium accessdecisions in a distributed manner.

4) Joint Channel Assignment and Routing: In this section,we present techniques considering the data link layer andnetwork layer jointly. Interference among the channels is oneof the main hurdle in achieving QoS in wireless networks.Orthogonal channel assignment is a potential solution to thisproblem. In [186], the authors present a joint algorithm forchannel assignment and routing. The proposed solution allowsthe creation of multiple routes in the network to achievehigher throughput. The channel assignment algorithm take intoaccount two factors: the first is network topology, while thesecond is information about the traffic.

VIII. MODERN NETWORK ARCHITECTURAL TRENDS ANDWIRELESS QOS

This section presents three types of modern network ar-chitectures. Various research areas of recent architecturesdiscussed in this section are summarized in Table VI.

A. Software-defined Wireless Networks (SWNs)

With increasing deployment and diversification of wirelesstechnology, managing wireless networks has become verychallenging. Software-defined networking (SDN) is a promis-ing architecture that can be used for conveniently operating,controlling, and managing wireless networks. The definingcharacteristic of SDN is generally understood to serve as theseparation of the control and data planes. The presence ofprogrammable controllers to adjust the operating parametersenables us to call these networks ‘software defined’.

Traditionally, networking devices, such as firewalls, routers,etc., require vendor-specific software for programming theiroperating parameters. This programming can be done manu-ally by a network administrator through the command lineinterface (CLI). This limits the margin of innovation thatcan be incorporated into the modern networks such as the

15

TABLE VISAMPLE OF RESEARCH ON QOS WITH RECENT ARCHITECTURAL DEVELOPMENTS

Project Description of QoS Enhancement Technique(s) References

Software Defined Wireless NetworksmeSDN Achieves real-time detection of QoS demands in a network and provides end-to-end QoS control. [187]QoSFlow Provides packet scheduling algorithm to improve QoS mechanism in OpenFlow/ SDN-based networks. [188]OpenQoS Provides a dynamic routing scheme that generates shortest path for data delivery in order to minimize packet

loss and latency.[189]

OpenFlow Controller for Multimedia Delivery Facilitates multimedia delivery with QoS using the best path with optimal service configuration. [190]FlowVisor Supports ‘QoS-enabled network slicing’ that provides a user or an application with a certain network capacity

“slice”, which is isolated from other coexisting slices servicing other users/networks.[191]

Multimedia Streaming QoS Architectures for SDN Provides QoS extensions for multimedia delivery using distributed control architecture in multi-operator SDNs. [192]Interference Mitigation in Enterprise WLAN Proposes an OpenFlow-based framework for interference mitigation in enterprise WLANs. [193]OpenFlow-based QoS support for Ofelia Proposes architectural extensions to make Ofelia a QoS-supporting federated experimental testbed. [194]PANE An SDN-based API for participatory networking was proposed that can be used by a user to reserve minimum

guaranteed bandwidth between two hosts.[195]

OpenQFlow Proposes a flexible variant of OpenFlow supporting a two-tiered flow-based QoS framework. [196]SDN for future Internet Proposed a SDN-based QoS framework that implemented a differentiation framework for OpenFlow networks.

The framework was tested in failure-conditions using single and multiple autonomous system scenarios.[197]

SDN control framework for QoS Programming of network devices to provide QoS guarantees. The SDN controller manages the traffic accordingto data collected.

[198]

AQSDN Proposed an autonomic QoS management mechanism for SDNs (AQSDN). The various QoS features inAQSDN are configured autonomically using OpenFlow and OF-config protocols.

[199]

FlowQoS FlowQoS is an SDN-based QoS framework comprising two components: firstly, a flow classifier mappingapplication traffic to different parts of flow spaces, secondly, a SDN-based rate shaper.

[200]

Cloud-based Wireless NetworksEDCA model for Cloud Proposes a model for QoS-aware differentiated multimedia cloud service provisioning in WLAN networks. [201]Resource Allocation in Clouds Proposes energy-aware resource allocation mechanisms for data centers set up in cloud environments. [202]Dalvi et al. Proposes centralized cloud-based approaches for managing WLANs. [203]CloneCloud Utilizes computation offloading through elastic execution between mobile devices and cloud. [204]LWAPP (RFC 5412) Proposes lightweight access point protocol (LWAPP) for centralized cloud-based WLAN management. [205]CloudMAC Enables APs to redirect MAC frames only. Processing of MAC data is done via cloud computing infrastructure. [206]IEEE 802.11 on Cloud-based Radio over Fibre Conducts a study on the feasibility of the architecture of IEEE 802.11 on cloud-based radio over fibre. [207]Cloud-based multimedia mobile streaming The proposed multimedia cloud computing solution considers the overall network environment and adjusts

the transmission frequency and multimedia transcoding parameters accordingly.[208]

Cloud-enabled Wireless Body Area Networks(WBANs)

Wan et al. have proposed using the hybrid of MCC and WBAN architectures to provide more reliable QoSto healthcare applications.

[209]

Cognitive Wireless NetworksCoexistence of 802.15.4 with IEEE 802.11 Proposes distributed adaptation strategies to ensure coexistence of IEEE 802.11 WLAN and IEEE 802.15.4

wireless sensor networks (WSNs) in the ISM band.[210]

Coexistence between IEEE 802.11b and IEEE802.16a networks

Proposes algorithms—based on dynamic frequency selection (DFS), power control (PC) and time-agility(TA)—to allow IEEE 802.11b and IEEE 802.16a networks to coexist in the same unlicensed band.

[211]

QoS-aware MAC for IEEE 802.11p Proposes an efficient multichannel QoS cognitive MAC (MQOG) for cognitive vehicular networks. [212]Integration of IEEE 802.11 and 3G Proposes schemes for integrating IEEE 802.11 and 3G seamlessly while satisfying QoS guarantees and roaming

agreements.[213]

Managing TCP in DSA-based WLANs Proposes a framework known as DSASync for improved end-to-end TCP performance in dynamic spectrumaccess (DSA) wireless networks.

[214]

Handover between IEEE 802.11b and overlay net-works

Proposes algorithms for intersystem handover between IEEE 802.11b and an overlay network while satisfyingthe QoS parameters of minimum data rate, maximum data block delay, and maximum BER.

[215]

world wide web or the WLANs. SDN changes this notion ofnetwork programming by extracting the control intelligencefrom the data plane and managing all the data plane devicesat centralized controller(s) [216]. Figure 3 shows a traditionalnetwork where the control and data planes are co-locatedin each networking device, and so the network control isdecentralized. In comparison, SDN has a centralized archi-tecture where the central SDN controller is controlling themultiple data planes; specifically, southbound APIs are usedto communicate with data plane, and northbound APIs areused to communicate with SDN applications. SDN providesthe flexibility of programming a network through the controlplane. This can help in simplifying network management andoperations. The rest of this subsection presents QoS efforts forIEEE 802.11-based SWNs.

QoS efforts for IEEE 802.11-based SWNs: Traditionally,SDN has been focused on campus and data center networks;but increasingly, researchers are also focusing on wireless

Fig. 3. Comparison of a traditional network and a SDN network architecture[217].

16

access networks. Since it can be difficult to manually configurevarious QoS knobs, OpenFlow and SDN architectures can bevery useful in automating scalable control of network QoSbased on high-level descriptions of application/service require-ments. For instance, Ferguson et al. [195] have proposedPANE that implements an API for participatory networkingusing SDN principles. PANE can be used to allow a userto reserve a certain guaranteed minimum bandwidth betweentwo hosts. The flexibility afforded by PANE can be used forenforcing QoS amongst other tasks (such as access control andpath configuration).

Numerous QoS works exploiting SDN principles and/or theOpenFlow protocol have been proposed. OpenFlow is the mostprominent SDN protocol used for implementing the architec-tural vision of separated control and data planes. OpenFlowimplements a protocol used by the SDN controller to commu-nicate with controlled devices. OpenFlow provides basic QoSprimitives including support of only FIFO scheduling whichmay be insufficient for some applications like multimediastreaming. QoS support for OpenFlow is improving: queuesare available in OpenFlow 1.0 which enables traffic shaping,while in the latest version, namely OpenFlow 1.3, rate limitingcan be supported through meter tables. The QoS routingsignificantly affects the overall throughput of a network. Themajor portion of Internet traffic is composed of best-efforttraffic. Therefore, an efficient QoS routing algorithm must takeinto account the existence of best-effort traffic and its impacton the overall performance. The OpenFlow controllers cangenerate flow tables to manage the QoS within a network usingdifferent routing protocols [218]. The controller performsadditional functions of QoS contract management and QoSroute management. The controller also polls switches to reporton the congestion level in the network.

Kim et al. [219] proposed an automated fine-grained QoScontrol approach for managing OpenFlow networks. In par-ticular, the proposed OpenFlow-based network QoS controlframework utilized per-flow rate limiters and dynamic pri-ority assignment. Another QoS solution called QoSFlow forOpenFlow-based SDN networks was proposed by Ishimori etal. in [188]. The proposed QoS solution relies on appropri-ate control of packet scheduling. In particular, QoSFlow isproposed as a QoS development strategy that relies on mul-tiple packet schedulers for OpenFlow supported networks toovercome the limitations of FIFO packet scheduling. QoSFlowcan provide control for the following packet schedulers: hier-archical token bucket (HTB), random early detection (RED)and stochastic fair queueing (SFQ). OpenQoS [189] is anOpenFlow controller designed for supporting multimedia flowswith end-to-end QoS requirements. It enables QoS by plac-ing multimedia traffic on QoS-guaranteed routes. OpenQoSpresents a new dynamic QoS routing scheme that maintains theshortest path for the data delivery, which helps in minimizingpacket loss and latency. The results show that the networkturbulence has a minimal effect on video quality with QoSsupport. On the other hand, the videos without QoS supportsuffer significantly from quality degradation.

In another OpenFlow-based work, Sharma et al. have pre-sented a QoS solution for the future Internet using SDN

technologies [197]. The SDN controller is used to config-ure the queues on the OpenFlow enabled routers. It usesthe Type of Service (ToS) field to enqueue packets in theappropriate queues at the edge routers. The routers identifyQoS requirement of the traffics and send them to appropriatequeues accordingly. The model is tested for both the singleand multiple AS environments to test the resilience in faceof network failures. In another work [198], an SDN-basedcontroller that uses the OpenFlow protocol is proposed toprovide the QoS guarantees to high priority flows. The solutionminimizes the degradation of best-effort traffic by using anew algorithm, which is based on resource utilization. Thepaper also shows the improvements brought about by theproposed algorithm on the traditional best-effort and IntServQoS schemes through experimental evaluation. In yet anotherOpenFlow-based QoS work, OpenQFlow [196]—a two tieredflow-based QoS framework was proposed. In OpenQFlow, theflow table is divided further into three tables: the first for theflow state, the second for the forwarding rules, and the final fordefining the QoS rules in which multiple micro-flows couldshare a single QoS profile.

There exists work in leveraging SDN principles for im-proved QoS performance in wireless networks. SDN-enabledIEEE 802.11 networks provide the benefits of agile QoSprovisioning. In an SDN network, bandwidth allocation, ratelimiting, and traffic shaping can be efficiently implemented atthe network level through automated QoS network APIs viathe network controller. Real-time measurements can help tosteer policies that can efficiently enforce the QoS mechanismsin real time [220]. QoS policies can be deployed at thecontroller and the wastage of resources can be minimized.In a SDN-enabled network, several controllers in a single areacan communicate with each other to exchange network infor-mation. This communication allows the users to connect withAPs, regardless of their operators, thus improving the user’squality of experience (QoE). An AP that receives packetswith a destination address of another network can forward thepackets flexibly through rules defined at the controller [221].Zhao et al. [193] have proposed a framework for a single SDNcontroller controlling all the APs via OpenFlow interface. Theproposed framework utilizes OpenFlow to mitigate interfer-ence in enterprise WLANs. The proposed framework addsspecific rules in various APs for packet scheduling withoutmodifying the conventional DCF mechanism. In another work,Lee et al. [187] extend the SDN controller network to mobiledevices. It helps in achieving real-time detection of QoSdemands in a network and can provide end-to-end QoS control.

In [190], Kassler et al. have proposed an SDN-based QoE-driven multimedia service negotiation and path optimizationarchitecture. In the proposed architecture, the QoS measure-ments are taken at the service level and the network level. Atthe network level, the data flows from a source to a destinationalong the same path. This helps the media to be delivered inthe best possible path and service configuration. In return, theoverall QoS for the users is improved. SDNs are proposed tocombine the configurations of network elements and end hosts.This enables network operators to define their own set of rulesto control the traffic routing and QoS. A dynamic framework

17

for ensuring QoS in streaming videos at the control planeis presented in [222]. The scheme works in the OpenFlow-based networks by optimizing forwarding decisions at theSDN controller. The controller acts as the brain of a networkwhere the forwarding decisions are made. The routing choicesare associated with the priority of the data flows. The resourcesare reserved at the controller, based on the type of delivery thecontroller can provide [223]. This reservation scheme does notaffect the other types of flows due to the dynamic routingmechanism in the OpenFlow architecture.

There also has been work on using SDN for QoS manage-ment of home networks. In [200], Seddiki et al. have proposedan SDN-based QoS framework called FlowQoS for managingthe QoS in home broadband networks. Using an SDN basedframework is helpful for managing home networks sincehome routers are typically feature constrained due to limitedcomputational capabilities. In addition, since users cannot beassumed to be networking experts, the QoS configuration isalso often too complicated for end-users. FlowQoS managesthis by outsourcing the QoS functions to a separate centralizedcontrol logic that allows a user to specify desired QoS policiesmore abstractly. More specifically, the FlowQoS frameworkcomprises two components: firstly, a flow classifier mappingapplication traffic to different parts of flow spaces, secondly,a SDN-based rate shaper.

SDN has also made it possible to bring autonomic capa-bilities in the network nodes. Such an approach is presentedin [199]. This approach proposes Packet Context-aware QoSmodel (PCaQoS) that configures various QoS features inOpenFlow switches by extending the OpenFlow configurationprotocol. This model checks the QoS requirements of thepackets and then forwards them into specific queues.

B. Cloud-based Wireless Networks (CbWNs)

The main idea of cloud computing is to offer computingservices (e.g., networks, storage, applications)—provisionedthrough APIs via the web from a shared pool of resources—ina virtualized data center in utility computing style [224]. Thecapability to program a network through the cloud/SDN archi-tectures allow revolutionary dynamism in service provisioning,network management and control. The trend of CbWNs isto extend the cloud computing concept to wireless networks[217]. An illustration of the CbWN architecture is shown inFigure 4. Some salient advantages of CbWNs are describednext.

• Centralized Management: A major application of CbWNsis centralized remote management of wireless networks.The control and provisioning of wireless access points(CAPWAP) protocol—defined by IETF in RFC 5415[225]—is a control and management (C&M) protocol thataims at migrating functionalities from the hardware APequipment to an external controller potentially managedvia the cloud. There exists significant interest in theresearch community in proposing efficient approaches forcentral management of Wi-Fi networks [203]. Variousindustrial solutions, such as Meraki Networks [226] fromCisco, Aruba Networks [227], and AeroHive, have also

Fig. 4. Cloud-based Wireless Networks (CbWNs) [217].

been proposed to perform cloud-based management ofWLANs.

• Zero-Touch Auto-Configuration: The centralized manage-ment paradigm of CbWNs can allow plug and play zero-touch auto-configuration of wireless APs allowing theAPs to function without any manual configuration bythe network administrator. The centralized managementof wireless networks also allow cloud-based performancemanagement and the use of advanced data analytics forperformance optimization including real-time reconfigu-ration of wireless parameters.

QoS efforts for IEEE 802.11-based CbWNs: Most of thedevices used for cloud computing applications are portableand are connected through IEEE 802.11 WLAN. The WiFiaccess network may not be able to cope with the need ofproviding services to QoS-assured cloud multimedia applica-tions. In particular, when the devices are in motion, QoS-awarehandover should take into account the traffic load and currentlyaccessible bandwidth at each location and at particular APwith high precision. Consequently, a precise modeling of thegenuine surroundings of IEEE 802.11 WLAN is important forproficient QoS-aware cloud service provisioning. Tursunova etal. proposed a pragmatic IEEE 802.11e EDCA model for QoS-aware differentiated multimedia cloud service provisioning inWLAN networks [201].

Most of the previous work concentrated on the analysis ofEDCA in saturated and non-saturated states. In [228] [229][230] [231] [232], the authors examine only clean channelsurroundings, with an assumption that the frame error iscaused by packet collision only, while in real surroundings,frame errors may take place due to channel noise. In [201],the authors considered the time-varying frame error probabilityof independent stations. They strengthened the mathematicalmodel of IEEE 802.11e [232] by using the calculated packeterror probability, which may be caused by frame collisions andchannel noise. Experimental outcomes show that the suggestedmodel gives more precise assessment, compared to existinganalytical models.

18

WLANs deployed by large firms or universities can com-pose of hundreds or even thousands of APs. Similarly the sizeof the operating system of an AP also increases with timedue to the inclusion of software packages in each release.Therefore, it is getting harder for the network administratorsto configure each AP individually. Reducing complexity ofnetworking appliances and uncovering data flow managementtasks via standardized interfaces and high-level programmingprimitives are some of the main concepts of SDN. In [202], theauthors present a resource allocation mechanism based on thecloud environments, as well as an energy-aware model for thedata centers. To obtain similar advantages in WLANs, Dely etal. introduced CloudMAC [206], which is a novel managementarchitecture in which access points redirect MAC frames only.The remaining functionalities, like the processing of MAC dataor management frames, are executed in typical servers thatare operated in data centers and can be allocated via cloudcomputing infrastructure. OpenFlow is used to organize theflow and transmission characteristics of MAC frames.

An emerging trend in cloud computing is the ‘mobilecloud computing’ (MCC) architecture that integrates mobileenvironments with cloud computing to enable mobile wirelessclients to perform computations in the cloud. Various QoSsolutions have been proposed for the MCC architecture. Chunet al. proposed CloneCloud which allows unmodified mobileapplications running in an application-level virtual memory(VM) to seamlessly offload part of their execution from themobile devices onto device clones operating in the cloud[204]. The ability to offload computation can be exploited ina QoS framework to meet stringent deadlines. Wan et al. haveproposed using cloud-enabled wireless body area networks(WBANs) for healthcare applications [209]. WBANs—whichare characterized by limited energy, memory, computation,and communication capabilities—can utilize the mobile cloudcomputing (MCC) architecture to remotely manage its pro-cessing requirements and provision QoS more reliably. In ad-dition, Wan et al. proposed that semantic models and ontologytechnology can be used to provide generic standard protocolsthrough which QoS may be assured. In another work, Lai et al.[208] have presented a network and device aware self-adaptiveQoS solution for cloud-based multimedia streaming suitablefor mobile devices. The proposed multimedia cloud comput-ing solution considers the overall network environment andadjusts the transmission frequency and multimedia transcodingparameters accordingly.

C. Cognitive Wireless Networks (CWN)Cognitive wireless networks (CWNs) are next-generation

wireless networks—that demonstrate network-wide intelligentbehavior—in which network nodes are incorporated with cog-nitive engines (see Figure 5) consist of substantial artificialintelligence (AI) approaches in the form of machine learning,knowledge reasoning, optimization, and natural language pro-cessing [233] [234]. Such networks are composed of networknodes equipped with cognitive radios (CR), which displaydevice-level intelligent behavior.

Along with network-level reconfiguration capabilities af-forded by technologies such as SDN which can be used to

Fig. 5. Cognitive wireless networks (CWN) include an embedded cognitiveengine which can observe network conditions, orient itself with the context,learn from experience, and decide to act [217].

realize programmable data plane and programmable controlplane, future wireless programmable networking will alsoimplement some variant of a “knowledge plane” [235]. Tra-ditionally, a network of nodes equipped with CRs is called acognitive radio network (CRN) with the dominant applicationof CR technology being dynamic spectrum access (DSA),which can resolve the ‘artificial spectrum scarcity’ problemresulting from the classic command-and-control licensing ap-proach [236] adopted in various countries around the world.Since CRNs inherently embody AI techniques with wirelesscommunications, it seems natural to explore using CRs toprovide mechanisms for implementing the knowledge planeof future programmable wireless devices.

While the bulk of CRN work has focused on enablingdevice-level intelligent behavior, the concept of CWNs, ini-tially proposed in [237], generalizes CRNs and emphasizesnetwork-level intelligence and self-aware behavior. While DSAis the most popularly cited application of CRNs, developingnetwork-level intelligence in CRNs enables numerous otherapplications—including the ability to reprogram itself opti-mally according to network conditions.

In previous CRN research, it has been observed that PHYand MAC layers offer many “knobs” that can be tweaked tooptimize performance which can be measured through some“meters”. In [236], many examples of knobs and meters atthe PHY and MAC layers have been provided. Since CRNsoperate in dynamic, often unknown, conditions, configuringthe knobs optimally is not a trivial problem. Various AI-basedtechniques have been proposed in the literature to assist CRNsin their quest of performing autonomous optimal adaptationsin such settings. Apart from AI techniques, CRN also borrowstechniques and tools from various other fields such as gametheory, control theory, optimization theory, metaheuristics, etc.[234].

Game theory has been used in various work to model,analyze, and develop QoS solutions for CRNs. Berlemannet al. [238] have proposed the use of radio resource sharinggames to enable distributed QoS solutions in unlicensed bandsshared by multiple users. Attar et al. proposed a game-theoreticresource allocation framework that guarantees QoS in a DSAenvironment (in which the primary network is assumed to be

19

OFDM-based cellular network). The QoS is defined by theminimum rate available to the primary network and the targetBER.

Optimization theory has also been used in the literature toaddress the problem of QoS-constrained dynamic spectrumaccess. For example, Xing et al. [239] considered QoS dif-ferentiation for various unlicensed users while incorporatinginterference temperature constraints assuming a spectrum un-derlay access (alternatively, known as a shared-use model). Inaddition, various cross-layered solutions have been developedfor ensuring QoS in CRNs. For example, Su and Zhang [240]proposed a distributed cross-layered solution incorporatingspectrum sensing at the PHY layer and packet scheduling atthe MAC layer for QoS provisioning in CRNs.

There has also been work in using cognitive technologiesto facilitate QoS-aware coexistence among multiple 802.11WLANs, between 802.11 and 802.16 networks [241] [211],and between 802.11 WLANs and overlay networks [215].

IX. OPEN RESEARCH ISSUES AND FUTURE WORK

QoS enhancement schemes in modern wireless-based net-works still need further attention. This section highlights someof the important issues.

A. Convergence of Different Technologies

Wireless technologies are proliferating at a breakneck pace,and in such a dynamic ecosystem, technologies that facili-tate multi-technology convergence is becoming increasinglyimportant. In the future, IEEE 802.11-based networks willincreasingly coexist with other wireless technologies suchas 4G/5G, WiMAX, RFID, Internet of Things (IoT), wire-less sensor networks, etc. As an example, 5G—expected tomaterialize by 2020—will be highly integrative and will tieWi-Fi with other wireless mobile standards such as 3G andLTE [242]. IEEE 802.11-based wireless networks is facingstiff competition from other technologies that coexist in theunlicensed spectrum space, such as the IEEE 802.16-basedwireless metropolitan area networks. Management of han-dover, spectrum sharing, coexistence, and interworking of di-verse technologies, become important for ensuring QoS. Therewill be a lot of interest in QoS-aware spectrum sharing andcoexistence between IEEE 802.11-based wireless networksand other technologies. This entails work at various layersincluding the potential use of multi-path TCP at the transportlayer for improving QoS by exploiting multi-homing witha diverse range of wireless networks, such as Wi-Fi and3G. More research needs to be done to ensure QoS in suchenvironments where heterogeneous technologies exist.

B. Context-Aware and Cognitive/ Semantic Computing

To improve the QoS and QoE, it is imperative for re-searchers to seamlessly incorporate user preferences, andawareness of context, which can be based on identity, location,time, or activity, into IEEE-based networks. Since the enduser’s traffic varies with time, traffic behavior should beanalyzed to predict the future traffic patterns and subsequently

to adopt appropriate strategies. This helps in fulfilling therequirement of end devices with higher efficiency. Also, sincethe wireless networks are mobile, predicting the future loca-tions of nodes helps in data forwarding, and thus in reducingthe overall delay. If the future location of a node can bepredicted from its mobility pattern and its speed, this helps insuccessful delivery of packets. Capturing the mobility patternsand its behavior ensure enhanced QoS.

Similar to the concept of cognitive networking, there isa rich literature of semantic computing and context-awarecomputing that can be used for developing QoS-aware solu-tions [243]. While traditionally focused on web services [244],and ubiquitous and pervasive computing environs [245], thesetechniques also are a good match for emerging architecturessuch as IoT, cloud computing, and global-scale machine-to-machine communication. QoS solutions in such environmentscan be enhanced by semantic support that leverages availablecontextual information. Recent work have proposed usingcontext-aware semantic service discovery and disseminationmethods to meet QoS requirements in such networks.

Although some work has been done in the design of QoS-aware cognitive routing [246] [247] and cognitive transportlayer protocols [214] [248] for CWNs, more work needs tobe done to realize the considerable promise of using AI-and machine learning-based techniques for developing IEEE802.11-based wireless networks that can provide high QoS andQoE.

C. Challenges due to Virtualization

Virtualization has transformed both operational efficiencyand the economics of the computing industry, and morerecently, the data center environment. With the growing roleof virtualization in networking, it is highly likely that IEEE802.11-based networks will increasingly utilize virtualizationtechnology in the future [217]. In particular, the combinationof cloud computing and network virtualization (includingnetwork functions virtualization) allow programmability thatleads to unprecedented flexibility in rapidly creating, deploy-ing, and managing novel services in virtualized settings asper the demands of users. This can create a new service-oriented architecture for wireless networking where hetero-geneous wireless access technologies including IEEE 802.11may coexist and converge as extended cloud infrastructure[249]. The QoS challenges associated with virtualization/cloudmanagement of IEEE 802.11 WLANs need to be investigatedthoroughly to resolve potential issues.

D. Exploiting Online Social Networking Information for QoS

An interesting direction of future work is to explore usinginformation and properties of online social networks (OSN) forQoS provisioning. OSN information can be used in the contextof QoS to predict and anticipate demand for resources as wellas provision of network resources. OSN information can alsobe used to develop policies that translate OSN relationshipsinto traffic engineering decisions—e.g., in community sharednetworks, OSN information can be used to provide differentQoS levels to different users based on their social relationship

20

(so that ‘friends’ get prioritized service over non-friends). Ina recent work, Sathiaseelan have proposed using OSN creden-tials for resource provisioning using SDN principles. With theincreasing role of OSNs—such as Facebook, Twitter—in mod-ern networks, the information in OSN provide rich metadatathat can be used profitably for efficient QoS implementations.

E. Fog Computing and QoS

The propensity of network architects towards centralizationand decentralization has seesawed over the past many years(cf. the change in focus from the mainframes to PCs to thecloud again). Fog computing is the latest architecture sustain-ing this trend. Fog computing is an emerging paradigm thatextends the cloud computing concept by bringing resourcesand services closer to the network’s edge [250]. Fog computingadvances cloud computing into the internet-of-things (IoT)era by descending the “cloud” and diffusing it to the end-user client devices. With the IoT architecture envisioning theconnectivity of billions of devices, the proposition of usingend devices for hosting services has become very attractive.

This migration of computation, control and storage fromthe cloud to the client devices has become possible dueto the advances in client device technology which is muchmore powerful than ever before. This allows applications torun close to the data, which is the key characteristic of fogcomputing that distinguishes it from cloud computing. Such anarchitecture is driven by increasingly stringent requirements ofmodern multimedia applications. Satisfying these requirementswith QoS will require augmentation of the traditional cloudcomputing model with the fog computing model as well asend user caching using concepts like information-centric net-working (ICN) [251] [252]. With fog computing implementedat the edge of the network, it provides an excellent frameworkfor enabling low-latency QoS-aware solutions [253].

X. CONCLUSION

It is anticipated that the bulk of access technologies in thenear future will be wireless. With emerging standards such as5G, and the convergence of the telecom and Internet industrieson IP-based technologies, the ability to provide high QoS hasbecome paramount. In this paper, we have surveyed variousQoS enhancement techniques proposed for IEEE 802.11-based wireless networks with our discussion encompassingboth classical techniques as well as proposals for new andemerging architectures such as SDN and cloud- networks. Wehave classified these techniques using different criteria. Wehave discussed QoS solutions that have been proposed forvarious TCP/IP layers along with a discussion on cross-layeredprotocols. We have also highlighted open research challengesand directions for future work.

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