A Multi-Pronged Approach to Adaptive and Context Aware ...

Mobile Networks and Applications manuscript No.(will be inserted by the editor)

A Multi-Pronged Approach to Adaptive and ContextAware Content Dissemination in VANETs

Joao M. Duarte · Eirini Kalogeiton · Ridha Soua · Gaetano Manzo ·Maria Rita Palattella · Antonio Di Maio · Torsten Braun · ThomasEngel · Leandro A. Villas · Gianluca A. Rizzo

Received: date / Accepted: date

Abstract Content dissemination in Vehicular Ad-hocNetworks (VANETs) has the potential to enable a myr-

Joao M. DuarteUniversity of Bern, Switzerland, IC, University of Campinas,BrazilE-mail: [email protected]

Joao M. DuarteIC, University of Campinas, Brazil

Eirini KalogeitonUniversity of Bern, SwitzerlandE-mail: [email protected]

Torsten BraunUniversity of Bern, SwitzerlandE-mail: [email protected]

Ridha SouaSnT, University of Luxembourg, LuxembourgE-mail: [email protected]

Maria Rita PalattellaSnT, University of Luxembourg, LuxembourgE-mail: [email protected]

Antonio Di MaioSnT, University of Luxembourg, LuxembourgE-mail: [email protected]

Thomas EngelSnT, University of Luxembourg, LuxembourgE-mail: [email protected]

Gaetano ManzoHES-SO, SwitzerlandE-mail: [email protected]

Gaetano ManzoUniversity of Bern, Switzerland

Gianluca A. RizzoHES-SO, SwitzerlandE-mail: [email protected]

Leandro A. VillasIC, University of Campinas, BrazilE-mail: [email protected]

iad of applications, ranging from advertising, traffic andemergency warnings to infotainment. This variety in ap-plications and services calls for mechanisms able to op-timize content storing, retrieval and forwarding amongvehicles, without jeopardizing network resources. Con-tent Centric Networking (CCN), takes advantage of in-herent content redundancy in the network in order todecrease the utilization of network resources, improveresponse time and content availability, coping efficientlywith some of the effects of mobility. Floating Content(FC), on the other hand, holds potential to imple-ment efficiently a large amount of vehicular applicationsthanks to its property of geographic content replication,while Software Defined Networking (SDN), is an at-tractive solution for the lack of flexibility and dynamicprogrammability that characterizes current VANET ar-chitectures. By implementing a logical centralization ofthe network, SDN enables dynamic and efficient man-agement of network resources.

In this paper, for a few reference scenarios, we il-lustrate how approaches that combine CCN, FC andSDN enable an innovative adaptive VANET architec-ture able to efficiently accommodate to intermittentconnectivity, fluctuating node density and mobility pat-terns on one side and application performance and net-work resources on the other side, aiming to achieve highQoS. For each scenario, we highlight the main open re-search challenges, and we describe possible solutions toimprove content dissemination and reduce replicationwithout affecting content availability.

Keywords VANETs · Content Centric Networking ·Content Dissemination · Floating Content · SoftwareDefined Networking · Content Caching · Replication

2 Joao M. Duarte, Eirini Kalogeiton, Ridha Soua, Gaetano Manzo et al.

1 Introduction

Vehicular Ad-hoc Networks (VANETs) allow communi-cations among vehicles and between vehicles and fixedinfrastructure, aiming to support a wide range of ser-vices and applications to make travel experience pleas-ant, safe, and informed [1]. Applications envisionedfor VANETs vary from traffic conditions and accidentwarnings to services such as live video streaming, livegaming, etc. The main technical challenges in VANETcommunications are related to the high dynamicityand volatility of the vehicular environment. Therefore,mechanisms for online adaptation of the network con-figurations to the wireless medium, to the highly vary-ing inter-user distance and to node density, etc. are re-quired. Though a lot of work has been done in proposingmechanisms for efficient content dissemination, it is stillan open issue how to reliably support infotainment andother video streaming related applications with accept-able Quality of Service (QoS).

This paper describes a possible approach to tacklethis issue, based on combining three paradigms:Content-Centric Networking (CCN), Floating Con-tent (FC) and Software-Defined Networking (SDN).Content-Centric Networking [2] allows messages to beexchanged throughout the network based on their con-tent and not on the location of the hosts. The CCNcommunication model is based on the exchange of In-terest and Data messages and is supported by threemain data structures: the Content Store (CS) to cacheincoming content, the Pending Interest Table (PIT)to keep track of Interest messages and the Forward-ing Information Base (FIB) to store communicationinterfaces. Figure 1 shows the basic architecture of aCCN node. In settings characterized by high node mo-bility and volatility, such as VANETs, CCN, due toits content centric but not host centric approach, maygreatly increase the chance of delivering the requestedcontent in case of disrupted links and frequent changesof network topologies [3]. However, adapting the rout-ing decisions to such changes is critical to achieve agood balance between optimizing content delivery like-lihood and resource utilization. In warning applica-tions, data packets are usually small and can be dis-seminated between vehicles equipped with On-BoardUnits (OBUs) and between vehicles and infrastructuresuch as Road Site Units (RSUs) without significantlyaffecting the available communication bandwidth. Forthese types of services, the push-based communicationapproach, usually adopted in publish/subscribe appli-cations, is well suitable. Therefore, Floating Content(FC), an opportunistic communication scheme, whichsupports infrastructure-less distributed content sharingover a given geographic area, could be a good candidatefor the implementation of these services.

Fig. 1: Architecture of a CCN node

The basic formulation of FC is push-based and sup-ports settings, in which a large fraction of nodes in agiven area (the Anchor Zone, AZ) are interested in re-ceiving small messages [4]. The idea is to store a givencontent in a spatial region without any fixed infrastruc-ture, making it available through opportunistic commu-nications to all users traversing that region. Whenevera node possessing a content is within the transmissionrange of some other nodes not having it, the content isreplicated. When a node with the content moves out ofits spatio-temporal limits, it deletes the content. Thecontent may be available on a set of nodes and movesover time within the AZ, even after the node that hasoriginally generated it has left the AZ. Thus, the con-tent ‘floats’ within the AZ. The ratio between this setand the total amount of nodes inside the AZ is calledAvailability. This value influences the probability thata node can get the content during its sojourn, whichis the Success Probability. Besides the advantages thatboth FC and CCN may bring in storing and dissem-inating content in VANETs, their performance couldbe improved by the coordination of a centralized entitythat has global knowledge of the nodes mobility, theirinterest in a given content, as well as other informations.This entity can properly set FC and CCN parameters(e.g. AZ size, time to replicate content, strategy for con-tent caching) and select which approach is more suit-able for a given use case [5]. Initially designed for wirednetworks, Software Defined Networking (SDN) has alsobeen recognized as an attractive and promising ap-proach for wireless and mobile networks [6]. These typesof networks can benefit from the flexibility, programma-bility and centralized control view offered by SDN, un-der different aspects, such as wireless resource optimiza-tion (i.e. channel allocation, interference avoidance),packet routing and forwarding in multi-hop multi-pathscenarios as well as efficient mobility and network het-erogeneity management. The pioneering SDN-based ar-chitecture for VANETs was proposed by Ku et al. [7],and afterwards enhanced [8,9] by adding cloud and fog

A Multi-Pronged Approach to Adaptive and Context Aware Content Dissemination in VANETs 3

computing components. In a scenario with a variety ofvehicular services with very diverse communication re-quirements, SDN holds the potential to improve themanagement of content delivery. A first Type-BasedContent Distribution (TBCD) method was proposed in[10] to improve content caching and forwarding in anSDN-enabled VANET. TBCD adopts a push-and-pullapproach for delivering content, based on the type ofcontent, and on the number of users interested in it.

The contributions of the present paper, which ex-tends our previous work [11], is threefold. First, it high-lights the potentials of using SDN in VANETs as wellas the relevant architectures that support SDN-enabledVANETs. This is of particular interest in understand-ing how CCN and FC could benefit from SDN featuresto optimize content dissemination in a network withintrinsic intermittent connectivity. Second, it analyzeshow several factors, such as mobility patterns, infras-tructure availability, network density, etc. can impactboth CCN and FC based content dissemination. Thepurpose is to provide insights on how the control ofthese parameters could enhance content delivery prob-ability. Finally, it investigates also how equipping vehi-cles with different technologies (e.g. Wi-Fi, LTE) mightreduce content retrieval time.

The rest of the paper is organized as follows. Sec-tion 2 highlights SDN benefits envisioned for vehicularnetworks and studies pertinent architectures proposedin the literature for SDN-enabled VANETs. Section 3describes how CCN and FC can be applied in vehicu-lar network scenarios. Section 4 envisages the researchareas where the use of an SDN controller may helpimproving the performance of CCN in vehicular net-works. Section 5 illustrates how FC can benefit fromsome form of coordination among nodes, when imple-mented through a SDN controller. Finally, Section 6concludes the paper.

2 Software-Defined Wireless Networking forVANETs: Benefits and Architecture

In this section we discuss the different architecturesthat were proposed notably for VANETs to overcomethe standoff of SDN deployment in intelligent trans-portation systems. Before that, we briefly outline theseveral benefits brought by SDN in terms of flexibility,abstraction and programmability.

2.1 SDN benefits in VANETs

SDN, first proposed in [12], is a paradigm based on thedecoupling of the data forwarding plane and the con-trol plane. The latter, which represents the intelligence

of the network, becomes logically centralized and pro-grammable, whereas mobile nodes become simple for-warding devices. Hence, data plane devices are releasedfrom carrying out complex operations and their mainfunction is restricted to only forwarding data accord-ing to forwarding policies prescribed by the controller.Hence, separating routing rules decisions from forward-ing actions allows dynamic access and administration.This dynamicity is required in VANETs since the envi-ronment around vehicles, including weather conditionsand neighbors, is continuously evolving and is shap-ing the behavior of vehicles. For instance, context- andlocation-driven routing updates requires dynamic pol-icy programming. However, dynamic policy program-ming cannot be supported by the classical VANET ar-chitecture. Moreover, in future 5G networks, connected”things” should operate in a seamless way enabling aplethora of applications. Current VANET architecturescannot cope with this explosive growth in device andradio access heterogeneity. Stemming from these obser-vations, we draw the main advantages expected fromenabling SDN in VANETs:

– Flexible Network configuration: The controllercan shape network behavior without going throughhard-coding of switches. The desired behavior istranslated into a set of rules that can be changedwhen necessary (e.g. prioritizing a specific data flow)according to requirements driven by VANET appli-cations [13]. Hence the controller might have coarse-grained control over the whole network while for-warding nodes may have local intelligence and applyfine-grained decision policies.

– Efficient network resource management:Since, the controller (implemented for instance inan RSU) has a holistic view of the network such asavailable bandwidth, spectrum resources, shortestand fast routes, it can intelligently decide at whichtime, what type of traffic will use a specific channelto avoid congestion and which route the data flowshould follow to meet delay, throughput and loadbalancing requirements. In absence of this intelli-gence, network resources could be jeopardized whenthe size of the network grows [14].

– Network heterogeneity support: In future 5Gnetworks, vehicles will be interconnected with ahuge number of devices on top of several networktechnologies. For instance, they will collect datafrom sensors deployed on streets, using different low-power network technologies (e.g. IEEE802.15.4 forshort-range, or LPWAN for long range). Besides,vehicles are envisioned to communicate also withcellular networks for bandwidth demanding traf-fic. Subsequently, vehicles are involved in a myr-iad of communications that are not straightforward


to support. SDN can overcome the heterogeneity ofdevices by seamlessly abstracting their differenceswith a unified managing control logic. This central-ized logic allows the discovery of devices and theiraccess to services in an abstract way. Moreover, SDNcan implement smart routing and traffic steeringover multiple network technologies to reduce packetdelivery time and increase throughput and reliabil-ity [13].

2.2 SDN architecture for VANETs

Figure 2 illustrates a typical SDN-enabled architecturefor VANETs, which is in line with those that have beenproposed so far in literature [7,13]. We now describe itsmain constituent parts:

• Data plane: Both stationary (RSUs, BSs) and mo-bile nodes (vehicles) constitute the data plane. Likewisefor other elements of the data plane, vehicles could beequipped with multiple radio technologies for controland data exchange.• Control plane: The control plane is logically cen-tralized. The controller collects the status of vehicles,RSUs, and BSs, which are abstracted as SDN switchesvia IEEE 802.11p or Wi-Fi beacons. The status includesvehicle location, speed, direction, neighbor informationand vehicles in coverage range of RSUs or BSs. Ba-sically, a RSU Controller (RSUC) communicates withdata plane elements and instructs them on forwardingrules or resource allocation strategies based on collectedstatus and current context of vehicles. In a fully cen-tralized operative mode (single controller), the archi-tecture is prone to the well-known drawbacks of tradi-tional wired SDN (e.g. presence of single points of fail-ure, loss of connectivity between RSUC and data plane,etc). Therefore, some distributed operative modes wereproposed to ensure scalability. A large VANET is par-titioned into clusters and each cluster is managed byits own controller. However, this zoning [14] is not ade-quate for computing optimal routes for packet delivery.In addition, controllers managing each cluster requiretight coordination to ensure performance across zones.An alternative is the hybrid architecture, in which thecontrol of the network is shared between the RSUC andthe local SDN agents that are installed in certain RSUsand vehicles. The controller sends an abstract policy toRSUCs or BSs and then RSUs decide about specific be-haviors depending on their local knowledge. An illustra-tion of rule forwarding operation is depicted in Figure 2.The intelligence as well as the complexity of networkcontrol are split between the RSUC and the distributeddata forwarding elements. Consequently, hybrid archi-tecture is more suitable to break scalability barriers.

Fig. 2: Hybrid architecture for SDN enabled VANETs

• Communication interfaces: To ensure that in-structions are received by data plane elements, controlplane and data plane communicate via a unified South-Bound Interface (SBI). One of the widely used SBI isOpenFlow [12], which is mainly conceived for wired net-works. In VANET scenarios, OpenFlow should be re-designed to adapt to nodes mobility and the intermit-tent connectivity in the data plane. Recently, an exten-sion of OpenFlow was proposed in [13], allowing vehi-cles to report positions and velocity. Nevertheless, notechnical details on how this extension is implementedare provided.

3 Content Dissemination in VANETs

The unique characteristics of VANETs and the hetero-geneity in communication requirements of vehicular ap-plications make it hard to find a general disseminationmechanism that performs well in all situations. Somerelated works already proposed CCN modifications toadapt the paradigm to VANET features. Goals were todecrease packet forwarding load and deal with difficul-ties in maintaining Forwarding Information Base (FIB)entries. For instance, Amadeo et al. [15], introduced anadditional field in the Data message to help requestersin selecting the best content provider. To increase con-tent availability, authors in [16] propose that each ve-hicle caches all received Data and forwards all Interestmessages to all available interfaces. However, increasingmessage size and forwarding multiple Interest messagesfor a given content increase traffic load.

3.1 Content Dissemination based on CCN and FC

The coupling between CCN and FC can provide suit-able adaptive solutions for content dissemination overVANETS. When content objects are bound to a spe-cific geographic region, and stored on all (or a subset of)nodes within the region itself, FC can play a key role for


improving CCN. By replicating content, FC introducesredundancy, which can be useful when nodes leave thearea or lose connectivity with their neighbors and hencedo not make content permanently available. Moreover,FC can make searching and finding content more effi-cient, if the geographic area of the floating content canbe derived from the content name. Normally, to retrievecontent, CCN requesters issue Interest messages includ-ing a content name describing the requested content. Toensure that the content bound to a geographic area isfound, the content name can be mapped to that area.Consequently, an Interest message is forwarded to thatgeographic area to meet the requested content. Map-ping can be supported by either having a geographicID in the content name or by having an intermediatenode, which translates the original content name into ageographic name. After the Interest has met a contentsource, a Data message including the content is sentback to the requester based on the stored informationin the PITs.

3.2 Adaptive Mechanisms for Content Disseminationin Vanets

Context parameters such as type of mobility, networkdensity, availability of RSUs along the path, propaga-tion models, etc. influence the operation of content dis-semination and retrieval mechanisms in VANETs andshould be taken into account. Therefore, we argue thata self-adaptive and context-aware mechanism for con-tent dissemination in VANETs, able to dynamically ad-just its network configurations, routing decisions, andanchor zone (AZ) characteristics is crucial and has thepotential to increase content delivery probability.

Furthermore, network configurations includingtransmission power and directions, data rate, packetlengths, etc. should be adapted to a set of specific pa-rameters such as the condition of the transmission chan-nel, the distance between nodes, node density and prop-agation models. For instance, in highways, straight-linepropagation may be observed while within a city ob-stacles such as buildings and other objects may causereflexions, deflections, refractions etc. In rural areas dif-ferent models may coexist.

Based on targeted performance metrics, routing andforwarding decisions should be programmed and up-dated. For example, when nodes are located close toeach other, a single transmission performed by the nodewith better reachability may be enough to disseminatecontent to all its neighbors. On the other side, whennodes are located far away from each other, a multi-hopapproach that minimizes the number of transmissionsand hence delay is needed. AZ shapes and sizes can beadapted according to the characteristics of each applica-

tion and current node density. For example, informationfrom a road condition warning application may be im-portant for vehicles within a radius of a few hundreds ofmeters while information from a traffic jam applicationmay be useful for vehicles within several tens of kilo-meters. In a highway scenario, a rectangular AZ shapeis more appropriate, whereas in a city center, square orcircular AZ shapes may reach more vehicles.

3.3 Content Distribution and Mobility

In this section, we discuss the various issues, parame-ters, and situations that can impact the performanceof content distribution mechanisms based on CCN andFC due to the mobility in VANETs. Efficient controlof these parameters is essential to maintain high con-tent delivery and retrieval probabilities while reducingthe number of Interest and Data messages collisions,retransmissions, duplicates and hence delays.

3.3.1 Mobility patterns

Mobility patterns are a decisive feature for content de-livery probability. The performance of disseminationmechanisms may vary according to source and receivermobility. We distinguish three cases in the following:• No mobility of the source and the receiver: Incases where there is no mobility of either source andreceiver, standard CCN Interest/Data exchange basedon CS, PIT and FIB can be used.• Mobility of the receiver: When receiver mobilityis present the following cases can happen:

(i) Low speed: In case of low receiver speed, stan-dard CCN Interest/Data exchange based on CS, PITand FIB still can be used, if the mobile receiver is stillin reach of the node to whom it sent its Interest mes-sage after one Interest/Data round-trip-time. This canbe estimated by considering distance between nodes,RSSI values, node speeds and directions, and RTT mea-surements.

(ii) High speed: In case of high receiver speed, thesoft state established by Interests in CCN routers cannot be used since the data traveling back following thePIT entries may not reach the requester anymore. Pos-sible solutions are:

In case of accurate mobility prediction, e.g. by nav-igation systems, public transport usage etc., and avail-ability of RSUs along the path: The task of contentretrieval is delegated to agents (see Subsection 3.5).Alternatively, the receiver can indicate its trace andestimated future positions and then, the source sendscontent to the estimated position. This might requireaccurate mobility prediction and possibly tracking ofmobile nodes.


In case of inaccurate mobility prediction or unavail-ability of RSUs along the path: Receivers can indicatea next destination in their path where to receive thecontent. Then, sources can send the content towardsthat destination and make the content float. The re-ceiver can then request it from there or from the orig-inal source or has to indicate a new location, e.g. if itchanges its path.• Mobility of the source: Source mobility can impactdrastically the probability that an Interest message sentby requesters will meet with at least one node able tosend back the requested data. For this, the followingpossibilities may be of use:

(i) The source can create an AZ for content thatis relevant to a certain area to store and advertise it.When leaving the created AZ, vehicles may then repli-cate the content in order to maintain it in that area fora certain time to live (TTL), established by the originalsource node.

(ii) Mobility prediction can be used to estimate thepath of the source and forward Interest messages to-wards the estimated source position.

3.3.2 Network density

Network density can range from dense networks, wherea huge number of nodes is available on a specific area, tosparse networks, where only few nodes are present. Indense networks it is important to use efficient duplicatesuppression mechanisms [17,18] to limit the amount ofconcurrent transmissions and thus decrease the proba-bility of collisions.

As the number of nodes in the network decreasesand the network becomes sparse, duplicate suppres-sion mechanisms become less crucial. However, in thesecases the probability of network disruptions increasesand efficient Delay-and-Disruption Tolerant Network(DTN) routing to ensure communication is required.Network disruptions can also happen in dense networks,e.g. in case of large unpopulated areas such as lakes,parks, etc.

3.3.3 Network partitions and temporal fragmentation

Network partition occurs when the number of vehiclesin the AZ is not sufficient to guarantee data dissemina-tion between vehicles. Temporal network fragmentationon the other hand refers to situations where commu-nications between vehicles are disrupted due to packetlosses, collisions or obstacles in the communication pathbetween a group of vehicles. The caching property ofCCN may be an efficient solution for these issues bysupporting the implementation of the so called ”store-carry-forward” mechanism, where vehicles can carry a

requested content and deliver it towards the requesterwhen an opportunistic link is available.

3.4 Multi-hop Content Retrieval

In several vehicular scenarios, some vehicles movinginto a given direction, along a main road or a highway,may be interested in retrieving content (e.g. videos)containing information about a distant location. Forinstance, fire trucks would be interested in receivingin advance videos of a fire to which they are heading,in order to estimate fire parameters such as severity,size, growth rate, etc., before reaching the intended lo-cation. In these cases, information received from videoscan proactively support efficient planning of the workto be carried on.

To request a video, a requester vehicle may send anInterest message towards the location where the videoshould be collected. However, getting immediately therequested video is not straightforward as one singlevideo is likely to be segmented into multiple chunksand therefore several packets may be transmitted in areduced time frame to deliver the whole video. On theother hand, the distance between the location of therequester at the time of issuing the Interest message,and the location where the video should be collected, islikely higher than the communication range of vehicles(i.e. few hundreds of meters if IEEE802.11p based com-munication mechanisms such as [19] are used). Thus, amulti-hop mechanism for dissemination of Interest andData messages is proposed. Neighbor vehicles are usedas intermediate nodes. However, only a subset of theintermediate nodes, may be selected to retransmit anInterest message in order to eliminate unnecessary re-transmissions.

3.4.1 Our approach:

We propose that Interest messages carry the type, nameand location of the requested content (e.g. video/ fire/latitude/longitude). Intermediate nodes when receiv-ing an Interest message will perform a lookup in theirCS and if the requested content is not available theywill schedule the retransmission of the Interest messagebased on an Interest timer. The values of Interest timersare calculated, taking as inputs the distance from theprevious sender and the expected time for which thevehicle will remains in the specific point of the road. Inthis case, vehicles that are located farther away fromthe previous sender and that will stay in the road forlong time will have shorter Interest timer periods.

When the Interest timer expires, the scheduled In-terest message is retransmitted and the PIT table isupdated by adding an entry related to the requested


data. The remaining intermediate nodes, when perceiv-ing that the Interest message has been retransmitted byanother vehicle (i.e. the vehicle with shorter timer du-ration), will cancel their scheduled retransmission.

When intermediate nodes receive an Interest mes-sage and find a copy of the requested data in theirCS, they automatically schedule the transmission ofthe Data message, using a Data timer (Data timers areshorter than Interest timers) and cancel the dissemina-tion of the Interest message. Among the intermediatenodes that contain the requested data the one locatedcloser to the requester node will have a lower Data timervalue and will be selected to forward the Data messageand therefore cancel both Interest and Data messagesscheduled by other nodes for that particular piece ofdata.

If none of the intermediate nodes find a copy of therequested data in their CS, the Interest message willeventually reach its intended destination. In this situ-ation, the vehicle geographically located closer to thedestination given in the Interest message will collectthe video and send it back towards the requester node.When intermediate nodes receive a Data message con-taining a piece of video, the data is first added to theCS. Then a PIT lookup is performed and if an entryrelated to that data is found the Data message is senttowards the requester and the PIT entry is eliminated.

3.5 Agent-Based Content Retrieval (ABCR)

Another approach for requesting and receiving contentis based on using agents. Requesters can delegate con-tent retrieval to one or more agents [3] and retrieve fromthem the content later. A requester broadcasts an Inter-est to potential agents, which respond by Data messagesdescribing their offer to retrieve content on behalf of therequester. The requester then confirms the agent selec-tion. Later, when the requester meets the agent again,it can retrieve the content using traditional CCN mes-sage exchange.

In a VANET, a user might like to retrieve a con-tent object from a location that is not in range, andwhere the vehicle is not scheduled to go. By letting re-quester and agent know their respective typical or ex-pected paths, the content source could select the rightagent (the one with the right path) for sending back thecontent object. Here we assume that the content sourceknows the path of the requester and of the candidateagents for carrying the content and that the contentsource will give information about the path of the re-quester to the agent carrying the content. Uncertaintyin space and time can make the rendezvous hard to beimplemented. To face this issue, the agent carrying thecontent could implement an AZ, in which the desired

content floats and that the requester will traverse withhigh likelihood.

Agents can also be used to come up with a solu-tion for receiver mobility without the need to modifyCCN. To address receiver mobility, a mobile requesterintending to visit an indicated area can delegate con-tent retrieval to an agent located in the indicated area.The agent requests the information from the contentsource and disseminates it using FC mechanisms in theindicated area. The mobile receiver then picks up thecontent from the agent or from another FC node whenvisiting the indicated area.

3.6 FC-assisted, Geographic Content Centric (DTN)Routing

In settings where volatility makes it unfeasible or inef-ficient to maintain a path between content requester(s)and content source, FC may be used to support so-called geographic content centric routing. We assumethat all nodes and content objects can be identifieduniquely, and that nodes know their location and fu-ture trajectory with some uncertainty. Such knowledgecould be derived from past spatio-temporal patterns.By letting each node share through FC its own dataon network state (e.g., node positions and trajectories,node content), FC can be used to build at each node acommon, shared representation of the network and itsevolution over time. Such representation could be usedto implement various strategies for DTN routing.

As a complement, when network density is sparseand/or the mobility of nodes does not allow to build astable path for content dissemination, Interest packetscould be made to float in an area around the originatornode. The floating content would be used as a ”fishingnet” to improve the chance of finding content amongpassing nodes. As a result, each node within an areawould then maintain and share a table (i.e., floatingPIT), describing a list of requested content objects. Foreach requested content object, the table stores a listof requesters. When meeting a node with one or moreof the requested content objects, those could be for-warded to the requesters using some form of DTN rout-ing scheme, possibly using the floating network state.

4 SDN Support for CCN in VANETs

In this section, we detail how content forwarding andcaching could be enhanced by coupling SDN and CCNin VANETs.


(a)

(b)

Fig. 3: SDN support for CCN forwarding in VANETs:(a) Forwarding of Interests along different paths, (b)Different forwarding strategies based on Interest names

4.1 SDN for CCN Forwarding and Broadcasting

In large-scale networks the size of FIB tables on eachCCN node can easily increase due to the large amountof exchanged content and the large number of contentsources. Alternatively, CCN routers can broadcast In-terest messages to neighbor nodes to request content.Subsequently, the possibility of congestion in pathsthrough the network can be very high. There have beenseveral attempts to encounter these problems; some ofthem try to identify a path between a requester and acontent source and store this path for future references[20,21]. A similar approach has been adopted also inCCVN [15], where messages are broadcast in the entire

VANET, but in case of collisions they are re-broadcastaccording to the distance from previous senders. To im-prove content retrieval, in [22] authors suggest to utilizethe different interfaces of a CCN node to transmit In-terests simultaneously through multiple interfaces. Forthe same aim, Udugama et al. [23] propose to split theInterest messages of the same request and send themthrough multiple paths at the same time.

An SDN controller, with its centralized view of thenetwork, can support the design of more efficient CCNforwarding strategies. For instance, a controller canbe responsible for selecting unicast paths between re-quester and content source in a given cluster of thenetwork [24]. To integrate SDN into CCN networks,Charpinel et al. [25] proposed a CCN controller thathas a complete view of the network. It defines the for-warding strategy, and installs forwarding rules in theFIBs of CCN routers. In every CCN router, there is aCache Rules Table (CRT). The CCN controller sendscache rules (replacement policies) to the CCN switches,which are stored in the CRT. The CCN router cachesthe content according to the rules that exist in the CRT.The presence of a centralized controller could be furtherexploited to improve CCN performance. For instance,an SDN controller can determine the number of chunksto transmit through a face and send them through mul-tiple faces simultaneously [26].

4.1.1 Our approach

As shown in Figure 3a, SDN could support the set upof multi-path communication. When a vehicle sends orreceives a message (Interest or Data), it could send (orreceive) it through multiple (redundant) paths. An SDNcontroller could discover several paths that satisfy In-terest messages of the same request. Then, the con-troller sends Interest messages through those paths inparallel to retrieve Data much faster.

In addition to path diversity, each vehicle could beequipped with diverse radio communication technolo-gies. For instance, a vehicle could have two or moreWi-Fi interfaces, together with LTE. Thereby, the re-quester could send two or more Interest messages si-multaneously to a local SDN controller [27]. Subse-quently, the controller could respond at the same timeto all these requests, since it could perform a multi-pathdiscovery mechanism. Hence, this multi-radio conceptwould optimize network resources and achieve shortercontent retrieval time. For instance, as shown in Fig-ure 3a, a requester sends three Interests to the SDNcontroller through three Wi-Fi interfaces. Afterwards,the controller that has already discovered available con-tent sources (in the previous step) sends these Interestson these multiple paths. Finally, the SDN controller


sends the retrieved Data back to the requester throughthe same interfaces.

In a CCN-based VANET, several applications willgenerate requests with different names. The networkmust treat these requests in a different way according toapplication requirements. For instance, a safety applica-tion generating warning messages should forward thesemessages to the entire network. On the contrary, an en-tertainment application sending video requests shouldforward these messages through an appropriate face inorder to find a content source. An SDN controller couldinstall such forwarding rules to make sure that eachmessage is treated differently, according to its name(Figure 3b). The overall geographic area is divided intoclusters, according to the location of the RSUCs. Foreach of these clusters, the RSUC is responsible for or-chestrating and managing network resources. Dividingthe network into clusters ensures more control and lesscomplexity for network administration. Besides, vehi-cles are considered as data mules: they perform store-carry-forward, enabling information to travel throughthe different clusters of the network. When a vehicleis between distinct RSUC areas, a push approach fortransferring warning Data messages to other vehiclescan be used.

Obviously, RSUCs could communicate with eachother by a wired connection. Bloom Filters couldbe used to advertise and exchange information be-tween RSUCs and hence to populate the FIB tablesof nodes [28]. The local RSUC that is responsible foreach geographic area, in addition to the forwarding andthe optimization of resources, could potentially pushmessages to vehicles These messages could be adver-tisements, safety messages or even local offers from thearea. Furthermore, vehicles equipped with different ra-dio technology interfaces select the appropriate tech-nology for transmitting each flow based on some QoSmetrics. For example, warning messages could use LTEto guarantee low latency and the high message deliveryrates required by safety applications.

4.2 SDN for CCN Caching

Caching enhances content discovery, retrieval and deliv-ery in VANETs by providing multiple sources (caches)of the content. However, the explosion of infotainmentapplications with their ubiquitous replicas creates anincreasing demand for the scarce spectrum in VANETs.Basically, caching is coupled with two fundamentalquestions: what content to cache and where to cacheit.

Caching all content along the delivery paths as sug-gested in [29] may cause serious performance degrada-tion. Even if the cache size is not a major concern inVANETs, it is not obvious if this cache can keep up

the pace with the increasing scale of multimedia con-tent distribution over VANETs. For these reasons, itwas proposed in [30,31] to cache only popular content(i.e. content which has been requested a number of timeequal or larger than a fixed Popularity Threshold, PT).Other works rely on the user interest for deciding whatcontent to keep [32] (i.e. nodes will cache only the con-tent they are interested in).

Concerning where to cache, one trivial solution is tocache replicas in every vehicle. The short-lived natureof links in VANETs, coupled with the time and space-relevant nature of content, accentuates the concernabout the selection of relevant nodes that can cachespecific content. Therefore, most new caching schemesattempt to reduce caching redundancy by only select-ing a subset of nodes in the delivery path. This subsetof nodes has high probability to get a cache hit andhence nodes in this subset are called ”central” nodes orinfluential nodes. Centrality-based solutions for nodeselection were proposed in the context of static net-works. However, their extension to highly mobile net-works, such as VANETs, is a thorny problem as cen-trality is not trivial[33]. Recent works [34,35] focus onthe social aspect of caching. Users in the same socialspace are likely to request the same content. Hence,the content is proactively pushed to the cache of users’proximate neighbors. The definition of these proximateneighbors is challenging. While in [34] proximate nodesare 1−hop neighbors, authors of [35] define these nodesas the nodes having a specific ratio of common contentitems with the user.

4.2.1 Our approach

An SDN controller could instruct Content Providers(CP) to trigger on-demand caching when popular con-tent has been identified. In the same way, the SDN con-troller could fix the value of the PT according to dif-ferent metrics. Moreover, the SDN controller, being theowner of the caching logic, will determine which vehiclesshould store replicas of the popular content at each pe-riod of time. These vehicles are called Content Cachers(CC). This centralized caching logic helps authoritiesto program and deploy the desired caching behavior.

Figure 4 illustrates an example of our proposedSDN-based caching approach in VANETs. Two RSUsare orchestrated by one RSU Controller (RSUC). EachRSU is covering a specific geographical area on a high-way. The RSUC fixes the PT and the set of influentialvehicles [36] in the zone. The set of influential nodes(i.e. nodes with better reachability than others) is time-variant since vehicles can enter and leave the networkfrequently. Therefore, the RSUC should periodically (orwhen needed) notify vehicles in the network about theupdated set of influential nodes. Once the number of


Fig. 4: SDN-based caching approach in VANETs.

requests for the content produced by the CP, reachesthe PT, the RSUC will trigger its caching spreadingstrategy. The popular content will not be sent to theimmediate 1-hop neighbors of CP like in [34], but willbe sent to the influential vehicles (as shown in Figure 4,CC1 and CC2). This mechanism avoids overloading thenetwork with replicas of the same content. The CP isaware of the set of influential nodes and sends themaccordingly the replicas. While CC1 is a 1-hop neigh-bor of the CP, CC2 is out of its transmission range.Therefore, the content is sent first to RSU2 and thenRSU2 forwards the popular content to CC2. Vehiclesinterested in the content of CP can ask CC1 or CC2

to retrieve it. Thus, vehicles far away from the CP (thenode that generated the original content) can get repli-cas by asking the nearest CC.

5 SDN support for FC in VANETs

In a real scenario, determining the minimal size andthe appropriate shape of the AZ to ensure high perfor-mance for FC (in terms of mean success probability, forinstance) is a complex task. Authors of [37] have proventhat the ratio between the AZ radius and the communi-cation range impacts information availability. Authorsof [38] provide the criticality condition, under whichthe content floats indefinitely over time with very highprobability. All such results are closely tied to a specificmobility model, and in particular, they depend heavilyon density, spatial distribution, speed and transmissionrange of nodes.

In addition, in the basic formulation of FC, contentreplication within the AZ does not take into accountneither the popularity of the content nor the size ofthe set of nodes carrying the content. This is criticalfor VANETs, where a massive number of messagesincreases both spectrum congestion and management

challenges.

5.1 Our approach

RSUC

RSU2

RSU3

UC

Accident

RSU1

(a) (b)

RSUC

Fig. 5: (a) SDN-based FC activation, (b) AZ reshapingin an accident intersection scenario

There are two main ways to estimate node densityand AZ size and shape: centralized and distributed ways.In the former one, a node in isolation and possessingneeded information defines the AZ. In contrast, in thedistributed way, nodes in a cooperative way, collect mo-bility information from their surrounding vehicles. Thisapproach provides more accurate estimation of param-eters such as density and average speed of nodes but re-quires longer time to converge. An attractive solution isto use a hybrid approach: the infrastructure (i.e. staticnodes) is used as support for FC, thereby increasing thequality of estimation of parameters and thus achievinga balance between message replication ratio and thedesired probability of success delivery.

To evaluate the success probability, several ap-proaches were proposed in the literature. A very firstapproach is modeling the AZ range in order to ob-tain a certain success probability (i.e. QoS) consider-ing all the other parameters (node density and spatialdistribution, node speed distribution, and transmissionrange) fixed. Taking into account a circular AZ, dif-ferent studies provide a well-posed success probabilityformula correlating with AZ radius. Some mobility pa-rameters are independent from the mobility model cho-sen (e.g. node density). The higher node density is, thehigher is the success probability, considering all theother mobility parameters fixed. Finally, setting theAZ radius could be done according to the node den-sity (values defined by the scenario considered). This


reshape could be achieved through infrastructure sup-port (e.g. SDN controller, which collects mobility in-formation such as speed and position of the vehicles inthe coverage range). Therefore, an efficient anchor zonecould be installed at the desired location. In a central-ized approach, RSUs are in charge of setting the rangeof the AZ. Even if the coverage of RSUs is large, it mayhappen that the covered area does not match with thearea of interest. Therefore a distributed approach maybe more suitable.

In environments with highly varying density, SDNcan ensure better persistence and availability of floatingcontent by accurately tuning the AZ size. This onlineadaptation of AZ saves network resources. Figure 5(a)shows a use case where an AZ is created on demand.An emergency vehicle enters the zone covered by RSU1

where there is no pre-established AZ. The emergencyvehicle asks RSU1 to define an AZ. Then the request isforwarded by RSU1 to the RSUC, which sends back theparameters of the AZ (shape, size, lifetime) based onthe content lifetime, density of nodes and mobility pat-terns. SDN can also be involved in reshaping an existingAZ. One interesting use case is information dissemina-tion in an intersection, which is a highly localized areaas depicted in Figure 5(b). To ensure that the contentis floating outside the AZ defined by the intersection,one possible solution would be to reshape the AZ andmake it larger. Even if this can be done without in-frastructure through a distributed approach, this latterdoes not guarantee a convergence to the desired results.However, as argued in [4], the bigger the AZ size is, thelower is the success probability (i.e. probability for anode entering in AZ to get the content), if node trans-mission ranges and density are fixed. Hence, the RSUCwill define a new AZ based on its global knowledge ofthe network. Content replication can also be supportedby infrastructure that provide an optimization of theestimation. The RSUC can define, through informationcollected from RSUs, the floating content priority. Sub-sequently, a node can decide to receive and/or ignorecontent, based on a priority rule that can take into ac-count the content lifetime, number of nodes replicatingthe content, and the intermittent nature of the connec-tions. Thus, the SDN controller implemented in RSUCcould figure out the content popularity and decide withwhich frequency the content is replicated.

6 Conclusions

Improving the probability of success in delivery andminimizing content retrieval time without jeopardizingnetwork resources are thorny problems in vehicular net-works, where V2V and V2I connectivity are intermit-tent and short-lived. In this work, we have identified

CCN and FC as two suitable enablers for improvingcontent storing, dissemination, and forwarding in fu-ture VANETs. Both should be adapted to the high dy-namic and volatile network environment. However, cur-rent VANET architectures suffer from lack of flexibilityand dynamic programmability. SDN, which decouplesthe control plane and data plane, is on the forefront ofpotential enablers of future VANETs, where routes canbe dynamically configured at a logical centralized con-troller, but not at each hop as in classical VANETs. Wediscussed the benefits of applying SDN in VANETs andthe features of SDN-enabled VANETs architectures. Weinvestigated also how SDN could provide support forCCN and FC (e.g. to select, according to node mobil-ity, the best paths to forward data packets, the influ-ential nodes where the content should be cached, or toactivate the AZ where the content should float).

Acknowledgments

This work was undertaken under the CONTACTproject, CORE/SWISS/15/IS/10487418, funded by theNational Research Fund Luxembourg (FNR) and theSwiss National Science Foundation (SNSF) project no.164205. The authors also would like to thank The Co-ordenacao de Aperfeicoamento de Pessoal de Nivel Su-perior (CAPES) and the Sao Paulo Research Foun-dation (FAPESP) for the financial support by grant2016/09254-3.

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