A Real-Time and Energy-Efficient MAC Protocolfor Wireless Sensor NetworksPardeep Kumar, Mesut Gunes, Qasim Mushtaq, Bastian Blywis

Institute of Computer ScienceFreie Universitat Berlin, Berlin, Germany

Email: {pkumar, guenes, mushtaq, blywis}@inf.fu-berlin.de

Abstract—This paper proposes AREA-MAC, a medium accesscontrol (MAC) protocol for wireless sensor networks (WSNs).AREA-MAC reduces latency and energy consumption of nodes byusing low power listening (LPL) with short preamble messages.Other protocols like B-MAC use long preamble messages thatcause higher latency, energy consumption, and control overheadon nodes. AREA-MAC provides a reasonable trade-off betweenvital parameters, such as system fairness, throughput, scalability,and adaptability to traffic conditions. Additionally, to minimizenetwork latency and maximize its lifetime, two application-basedoptimization problems are formulated. The gain of AREA-MACin terms of delay and energy efficiency and an OMNeT++ basedsimulation framework are also discussed.

I. INTRODUCTION AND MOTIVATION

MAC protocols for WSNs [1], [2] have to deal with moreissues than for traditional wired or wireless networks. Time-liness and energy efficiency are some of those. The directinteraction of WSNs with the real world, where physical eventsoccur in an unpredictable manner and the duty-cycling ofradio make real-time guarantees more challenging. Collisions,overhearing, control packet overhead, idle listening, and over-emitting cause energy waste in WSNs [3]. An ideal WSNMAC protocol specifies how nodes share the channel, responseto the inquirer timely, and save energy to survive for a longerperiod. In addition, it ensures high throughput, low overhead,low error rate, scalability, and graceful adaptation to topologychanges.

Most of the MAC protocols for WSNs [4]–[12] are mainlydesigned for a single main objective - energy efficiency.Other parameters such as low-latency, adaptability to trafficconditions, scalability, and bandwidth utilization are mostlyignored or dealt with as secondary objectives. For medicalurgency, surveillance, home automation, flood, fire, and seis-mic detecting applications, the provision of real-time guaran-tees is as crucial as saving energy. This paper proposes theAsynchronous Real-time Energy-efficient and Adaptive MAC(AREA-MAC) protocol for WSNs to support real-time andenergy efficient applications. It provides application-specificoptimized performance in terms of timeliness and energyefficiency, while maintaining an acceptable system fairness andtrade-off between different parameters. AREA-MAC uses LPLwith short preamble messages, where nodes wake up shortlyto check the channel activity and destination address writtenon the preamble. They go back to sleep mode immediately, ifthe address does not match.

The remainder of this paper is organized as follows. InSection II, the state of the art is briefed. Subsequently, inSection III, AREA-MAC is introduced and network, energy,and delay models are discussed. Further on, two separateoptimization problems for delay-bound and energy-efficientscenarios are formalized. Afterwards, in Section IV, a sim-ulation framework for AREA-MAC is described. Section Vconcludes the paper.

II. RELATED WORK

MAC protocols for WSNs can be classified into the twobroad categories of contention-based and schedule-based pro-tocols. In contention-based MAC protocols nodes compete toacquire the channel. In scheduling-based protocols, a scheduleregulates which participant may use which resource at whattime. In this section, well-known MAC protocols from bothcategories are briefly discussed. A detailed discussion of theprotocols is given in [3]. Table I compares them regardingtheir support for timeliness, energy-efficiency, synchroniza-tion, adaptability to traffic conditions, and scalability factors.

S-MAC [4] circumvents idle listening, collisions, and over-hearing by using periodic and fixed-length wake-up and sleepperiods, but it is rigid and optimized for a predefined set ofworkloads. Synchronization and longer sleep periods resultin higher latency. Time-out MAC (T-MAC) [10] protocolimproves S-MAC by adaptively shortening the listen period bymonitoring for a threshold period. T-MAC suffers from earlysleeping, reduced throughput, additional latency, complexity,and scaling problems. The CSMA based B-MAC [12] protocoluses low power listening (LPL) with an extended preamble toreduce duty cycle and idle listening. It has an overhearingissue and the long preamble dominates the energy usage.The TDMA based LEACH [5] divides a WSN into clusters,each supervised by the cluster-head. Always-on cluster-headsand scalability are major problems with LEACH. The IEEE802.15.4 standard [13] provides several features for WSNs.But it also carries limitations, especially for real-time, energy-efficient, and bandwidth critical WSN applications, identifiedin [14].

III. AREA-MAC

The main object of AREA-MAC is to provide a suitablesolution for time critical and energy-efficient applications and,at the same time to provide an acceptable trade-off between

978-1-4244-3474-9/09/$25.00 ©2009 IEEE

TABLE ICOMPARISON OF DIFFERENT WSN MAC PROTOCOLS

REGARDING THEIR SUPPORT FOR TIMELINESS [A], ENERGYEFFICIENCY [B], ASYNCHRONY [C], ADAPTABILITY [D] AND

SCALABILITY [E] FACTORS.Protocol [A] [B] [C] [D] [E]S-MAC [4] no yes* no no noT-MAC [10] no yes no yes* noDSMAC [9] yes* yes* no yes noB-MAC [12] no yes yes yes yesSTEM [8] yes* yes* yes* no noTRAMA [6] no yes no yes noLEACH [5] no yes* no no noWiseMAC [7] no yes* yes* yes* no802.15.4 [13] yes* yes yes* no yes*

AREA-MAC yes yes yes yes yes* Partial support which also includes dependency of a pa-rameter on topology or trading-off with an other parameter.

other vital parameters. The main characteristics of AREA-MAC are:

1) Asynchrony: As system-wide synchronization results inoverhead and scaling problems, the nodes using AREA-MACare fully independent of the sleep and wake-up schedules ofother nodes. However, for better routing and link cost measure-ment, which is discussed later, the nodes save wakeup-sleepschedules and energy information of their 1-hop neighbors.

2) Energy-efficiency: AREA-MAC uses the LPL approachwhere nodes wake up very shortly to check the channel activitywithout actually receiving the data. They go back to sleepmode if the channel is idle; otherwise they receive data. TheMAC protocols [7] and [12] use the LPL with long preambles,where nodes remain awake for the whole preamble time evenif they are not target1 nodes. However, nodes using AREA-MAC have short and adaptive preambles with the destinationaddress and an acknowledgement combination, also suggestedby [15]. This combination solves many of the issues whicharise with long preambles, such as energy consumption bothat the receiver and sender sides, overhearing at non-targetreceivers, and excessive latency at each hop [11]. Nodes usingAREA-MAC wake up shortly to check the medium. If apreamble is found on the medium, they match their addresswith the destination address of the preamble. On a match, thenode acknowledges the sender immediately, which causes thesource node to stop sending further preambles and to starttransmitting data packets. All non-target nodes go back tosleep mode immediately which minimizes the possibility ofa collision, idle listening, and overhearing.

3) Real-time support: For real-time data, the source noderequests/forces the suitable next-hop neighbor to wake upregardless to its normal schedule. The quick response fromthe intended target node almost eliminates the possibility ofdelay and over-emitting. The suitable neighbor is selected onthe basis of a link cost metric.

4) Adaptability: Nodes may change their duty cycle ac-cording to the real-time request received from their neighbors.

1A forwarding node which has just received a packet, but is not the finaldestination.

�����

��� ��� ���

�� ��� ���

�� ��

�� �� �� ��

������� �������

�����

�����

�����

����� ����� �����

�����

�����

����� ����� �����

�����

�����

�����

�

�� �

�����

���

Fig. 1. A portion of grid-based WSN

On reception of such request, the target node responds andadapts its duty cycle accordingly. Moreover, AREA-MACis scalable and robust to topology changes. Unlike cluster-based approaches, where nodes only communicate via clusterheads, nodes using AREA-MAC communicate directly withpeers and exchange their wakeup-sleep schedules and energyinformation.

A. Assumptions

We consider a grid-based WSN shown in Fig. 1, consistingof several nodes and terminating at the sink node. All nodesexcept the sink node are normal nodes that sense, transmit, andreceive. They have no aggregation or in-network capabilities.We assume that all nodes are fixed and know their locationsregarding to some reference nodes. The selection and workingof reference nodes is out of our scope. We assume that thedensity of nodes is high enough, so that a node can directlycommunicate with multiple neighbors. All nodes carry uniquenode IDs and are deployed in an ascending order with asink node having the highest deployment level. Normal nodesforward data only to up-level direction, i.e., towards sinknode. We also assume that the sink node does not have anyenergy limitations, whereas other nodes have limited and non-replicable energy resources.

B. Network Model

A WSN is represented by an undirected graph G(V,E),where V = {v0, v1, ..., vN−1} is the set of N sensor nodes’IDs and E is the set of edges connecting those nodes. Suchgraph can be described as a grid topology of m × n orderwith m rows and n columns. Nodes are placed at the location(x, y), where 1 ≤ x ≤ m and 1 ≤ y ≤ n, as shown in Fig. 1.Given the node ID, its location can be calculated easily andvice-versa [3]. The node v0 represents the sink node, whereasnodes from v1 to vN−1 represent normal sensor nodes. TableII shows all terms used for the network model. An up-level

TABLE IITERMS USED FOR NETWORK AND ENERGY MODEL

Symbol Used forN Total number of sensor nodesN1vi

, N2vi

1-level and 2-level neighbors for viδvi Degree of vi∂vi,vj Euclidean distance between vi and vjCvi,vj Connectivity between vi and vjFvi,vj Data flow from vi to vjRvi Residual energy of viLvi Last wake-up time of viTχ, Pχ Time and power in the respective stateTaχ Average time in the respective stateTrxdata, Ttxdata Time to RX/TX a data packetTrxhello, Ttxhello Time to RX/TX a hello packetTrxpre, Ttxpre Time to RX/TX a preambleTbyte Time to RX/TX one byteTack Time for an acknowledgementTsw Time for radio switchingIwakeup Wake-up intervalIhello Hello intervalTH1 Threshold for link costTH2 Threshold for energy consumption

neighbor of a node vi is called an 1-level neighbor for vi, if itslocation parameters (x, y) satisfy one of these three conditions:

1) If its x value is equal to the x value of vi, then its yvalue should be one less than y value of vi.

2) If its y value is equal to the y value of vi, then its xvalue should be one less than x value of vi.

3) Both x, y values are one less than the x, y values of vi.Similarly, an up-level neighbor of a node vi is called a 2-

level neighbor for vi, if its location parameters (x, y) satisfyone of these three conditions:

1) Its x value is two less than the x value of vi.2) Its y value is two less than the y value of vi.3) Both x, y values are two less than the x, y values of vi.The set N1

vicontains all 1-level neighbors and N2

vicontains

all 2-level neighbors for the node vi. For example, in Fig. 1,N1v10 = {v5, v6, v9} and N2

v10 = {v0, v1, v2, v4, v8}. Eachnode vi ∈ V has a limited transmission range, but it caneasily communicate with all of its N1

viand N2

vineighbors. The

degree of vi, is given by δvi= N1

vi+N2

vi, hence δv10 = 8 in

the above example.

C. Energy Model

We consider two types of WSN traffic generating scenarios;a periodic, where nodes generate data with fix periodic intervaland an aperiodic, where nodes generate data at random inter-vals. The later is used for real-time applications, where data isgenerated in an unpredictable manner. As the sink node doesnot have any energy or storage restriction, the energy model isapplicable only to normal nodes. First, we calculate the energyconsumption of a node for periodic traffic.

In order to save energy, nodes use the LPL approach andare most of time in sleep mode. We divide the system timeT in small discrete time intervals, t0, t1, ..., tn. For simplicity,all time intervals are normalized to one time unit. The totalenergy consumption of a node vi per unit of time, Evi , is given

by its energy consumption in LPL, carrier sense, environmentsense, reception, transmission, and sleep states respectivelyand shown in (1). Equation (2) shows power consumption andtime spent by a node in the respective state for the respectivetime interval.

Evi = Elpl + Ecarrier + Esense + Erx + Etx + Esleep (1)= PlplTlpl + PcarrierTcarrier + PsenseTsense

+ PrxTrx + PtxTtx + PsleepTsleep(2)

A node performs LPL at every wake-up interval and sensesthe carrier before sending a preamble. It also senses theenvironment to measure physical values such as temperature,humidity, air velocity, and light.

Tlpl = Talpl/Iwakeup (3)Tcarrier = TacarrierRdata (4)Tsense = TasenseRsense (5)

Where Rdata is the rate at which the node sends andreceives data packets and Rsense is the rate at which it sensesthe environment. The transmission time of the node is the sumof time required to send data packets, preambles, hello packets,and acknowledgement. At every hello interval, a node sends ahello packet. Whenever, it has data to send, it sends a preambleand immediately changes its radio to listen mode in order toreceive the acknowledgement. This process is repeated until itreceives an acknowledgement from the target node. Q is thenumber of attempts a node sends a preamble and changes itsradio to receive an acknowledgement and P is the maximumnumber of allowed attempts, such that 0 ≤ Q ≤ P .

Ttx = Ttxdata +Q (Ttxpre + Tsw) + Tack + Ttxhello (6)Ttxdata = LdataRdataTbyte (7)

Ttxhello = (Lhello/Ihello)Tbyte (8)

Where Ldata and Lhello is the total length of data and hellopacket in bytes respectively. A node may receive multiplepreambles during a time period. But when it becomes atarget node for an specific preamble, it immediately sends anacknowledgement to the sender and receives its packet.

Trx = Trxdata +∑

Trxpre + 2 Tsw + Tack + Trxhello (9)

Trxdata = LdataRdataTbyte (10)Trxhello = (Lhello/Ihello)Tbyte (11)

A node is supposed to be in sleep mode, if it is not doinganything else.

Tsleep = 1− (Tlpl + Tcarrier + Tsense + Trx + Ttx) (12)

For aperiodic traffic, the important aspect is to decide for thewake-up interval for a node. We calculate this on the basis of

Poisson distribution and calculate the expected number of real-time events occuring in an interval. If the rate of occurrenceswithin an interval is λ, then the probability that there areexactly k occurrences is given by (13). For every occurrenceof k, a node wakes up and performs data processing.

f(k;λ) =(λke−λ

)/k! k ≥ 0 (13)

System Lifetime: It is difficult to have a precise criterionto define WSN lifetime. There exist many lifetime definitions,such as the time when the first node dies, the time somefraction of nodes die, or the time that the network partitionsin two or more segments. We use a more general definitionof lifetime, namely as the time the network is able to provideapplication-specific services. Therefore, in order to maximizesystem lifetime, we simply minimize the energy consumptionat each node vi.

minvi∈V

Evi i > 0 (14)

D. Delay Model

The long sleep duration of LPL results in higher latency forWSNs. In AREA-MAC, all nodes are fixed and know their up-level neighbors. Therefore, in case of real-time data, a noderequests/forces an up-level neighbor to wake up regardlessof its normal schedule and to perform data processing. Thesuitable up-level neighbor is selected on the basis of link costmetric. The link cost for sending a real-time packet from vito vj , i.e., LCvi,vj

, is a function of total (expected) delaybetween vi and vj , distance between vj and the sink node v0,residual energy of vj , last time it was in wake-up mode, andthe number of up-level neighbors of vj . The parameter relatedto the last wake-up time ensures that all nodes get a fair timeto be in sleep mode and brightens chances for all nodes todie at almost the same time. All link cost parameters havedecreasing priority from left to right.

LCvi,vj={Dvi,vj

, ∂vj ,v0 , Rvj, Lvj

, δvj

}(15)

The total delay required to transfer a packet from vi tovj , i.e., Dvi,vj

can be divided into three steps; delay at thesource node vi, delay at all intermediate nodes vf , and delayat the destination node vj , each denoted by Dvi

, Df , and Dvj

respectively. If the set F contains all forwarding nodes suchthat vf ∈ F ⊂ V , the processing delay at each node is Tpro,and the queuing delay is Tque then:

Dvi= Tlpl + Tsense + Tcarrier + Ttx + Tsw + Tpro (16)

Df =∑vf∈F

Tlpl + Tcarrier + Trx + Ttx + Tsw + Tpro + Tque

(17)Dvj

= Tlpl + Tcarrier + Trx + Tsw + Tpro + Tque (18)Dvi,vj

= Dvi+Df +Dvj

(19)

E. Formulation of Optimization Problems

In order to achieve an optimized performance of AREA-MAC in terms of energy efficiency and timeliness, two sepa-rate optimization problems (OPs) for the periodic and aperi-odic traffic scenarios are formulated. Periodic traffic containsroutine data and is not usually critical in terms of delays.Therefore, the objective in such scenarios is to save energy(OP-1). However, aperiodic traffic is generated on the basis ofsome unexpected events which occur in the sensing area and isusually very critical and needs strict timeliness requirements.In such scenarios, the objective function is to minimize theoverall network delay (OP-2). For periodic traffic, nodes senddata to 1-level and for aperiodic traffic, to 2-level neighbors.

OP-1min Evi vi ∈ V ; i > 0

subject to:∑Cvi,vj > 0 vi, vj ∈ V ; i > j (20a)∑Fvi,vj ≥

∑Fvk,vi vi, vj , vk ∈ V ; k > i > j (20b)

Evi ≤ TH2 ≤ Rvi (20c)Cvi,vj ∈ {0, 1} (20d)Fvk,vi , Evi , TH2, Rvi ≥ 0 (20e)

OP-2min Dvi,vj vi, vj ∈ V ; i > j

subject to:∑Cvi,vj > 0 vi, vj ∈ V ; i > j (21a)∑Fvi,vj ≥

∑Fvk,vi vi, vj , vk ∈ V ; k > i > j (21b)

LCvi,vj ≤ TH1 vi, vj ∈ V (21c)Cvi,vj ∈ {0, 1} (21d)Fvk,vi , LCvi,vj , TH1 ≥ 0 (21e)

Constraints (20a) and (21a) show that each node must beconnected to at least one up-level neighbor, that may includesink node. Constraints (20b) and (21b) assure that the data flowsent by a node should be at least equal to what it has receivedfrom its low-level nodes. The constraint (20c) restricts totalenergy consumption and (21c) restricts delay conditions. Bothof these values should not exceed their respective thresholds.Binary variables in (20d) and (21d) represent the connectivitybetween vi and its neighbors, whereas (20e) and (21e) arenon-negativity constraints.

F. Time and Energy Saving of AREA-MAC

Fig. 2 indicates an obvious gain of AREA-MAC in terms ofenergy and time over the traditional long preamble approach.The gain is not limited to sender and receiver; non-target nodesalso benefit. A node wakes-up shortly to sense the carrierand check the preamble. If preamble is not for that node, itgoes back to sleep mode immediately. Moreover, for real-timetraffic, where the sender directly requests its 2-level neighbor

����

����

����

����

����

���������

����

���������

�����

�����

����

�������

���������

�����

�����

����

�������

�������������������������

�������������������������

������������

��������� �

��!��"���#��� � ���$����%�"�&�'������ '�!���

���

(���

(���

(���

(���

(���

���������

�����(���

Fig. 2. AREA-MAC gain in terms of time and energy over the traditionallong preamble approach.

to wake-up, gain is 100% for non-target nodes. This furtherhalves latency and saves more energy at 1-level neighbors.For this, a node needs more transmission energy but that ismuch less than the energy consumption at 1-level neighborsto wake-up and process data.

IV. SIMULATION FRAMEWORK

The detialed-view of a node using AREA-MAC frameworkis depicted in Fig. 3. This framework is based on OMNeT++simulator [16]. The Optimize model reflects optimization interms of latency, energy efficiency, and link cost depending onthe application selected in the Utility model. The Stack modeldefines the working at different layers, whereas the Blackboardmodel deals with internal components of a node and cross-layering functionalities. The Comm model helps in selectingup-level neighbors and collecting link cost values from the op-timize model. To make simulation close to reality, appropriatepropagation, modulation, sensing, and noise algorithms can beused in the Environment model.

V. CONCLUSION

This paper proposes AREA-MAC, a MAC protocol forWSN, which deals with time and energy critical applications,while maintaining reasonable system fairness. The protocoluses LPL approach with short preambles to solve the issuesof excessive latency, energy consumption, and overhead. Net-work, energy, and delay models are discussed in detail. More-over, to minimize network delay and to maximize its lifetime,two optimization problems are derived. An OMNeT++ basedsimulation framework for AREA-MAC is briefly discussed.Preliminary result indicates for an obvious gain of AREA-MAC in terms of energy and time over the traditional longpreamble approach. Future work includes implementing andcomparing AREA-MAC with state of the art protocols for end-to-end delay, energy consumption, throughput, adaptability,scalability, and bandwidth efficiency metrics.

���������

���

�����

�

�����

��� ��� ���

�����

�� � ������

������ �

��� ��� ��

��������

��������

������

������� � ��

��������

����������

�����

���� ��

��� � ��

�����������

��� �� �

��� �� ��

����

������ �

�� ��!��

������"�

�� ��!��

� �#�����

��� ����������

$�� � ������� �� ��������

���������

������ ��

%��&'�!���

�(���)��

$(���)��

���� ��

����������

���

��*

�����

� +�� ���

��� �����

��� � �

���

� �#�����

,�����

�������

Fig. 3. An internal view of a node for an AREA-MAC simulation framework.

REFERENCES

[1] M.Tubaishat and S. Madria, “Sensor networks: an overview,” IEEEPotentials, 22(2):20–23, April 2003.

[2] H. Karl and A. Willig, Protocols and Architectures for Wireless SensorNetworks. John Wiley and Sons Ltd, 2006.

[3] P. Kumar and M. Gunes, “MAC protocols for low-latency and energy-efficient WSN applications,” Tech. Rep. TR-B-08-18, FU Berlin, Ger-many, December 2008.

[4] W. Ye, J. Heidemann, and D. Estrin, “Medium access control withcoordinated adaptive sleeping for wireless sensor networks,” IEEE/ACMTrans. Net., vol. 12, no. 3, pp. 493–506, June 2004.

[5] W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Anapplication-specific protocol architecture for wireless microsensor net-works,” IEEE Transactions on Wireless Communications, vol. 1, no. 4,October 2002.

[6] V. Rajendran, K. Obraczka, and J. J. Garcia-Luna-Aceves, “Energy-efficient, collision-free medium access control for wireless sensor net-works,” ACM SenSys, Los Angeles, CA, Nov, 2003.

[7] A. El-Hoiydi and J. Decotignie, “WiseMAC: An ultra low power macprotocol for the downlink of infrastructure wireless sensor networks,”Ninth IEEE Symposium on Computers and Communication, ISCC04,pp. 244–251, June 2004.

[8] C. Schurgers, V. Tsiatsis, S. Ganeriwal, and M. Srivastava, “Optimizingsensor networks in the energy-latency-density design space,” IEEEtransactions on Mobile Computing, vol. 1, no. 1, pp. 70–80, 2002.

[9] P. Lin, C. Qiao, and X. Wang, “Medium access control with a dynamicduty cycle for sensor networks,” IEEE WCNC, vol. 3, pp. 1534–1539,March 2004.

[10] T. van Dam and K. Langendoen, “An adaptive energy-efficient macprotocol for wireless sensor networks,” 1st ACM Conf. on EmbeddedNetworked Sensor Systems (SenSys), pp. 171–180, Nov. 2003.

[11] M. Buettner, G. Yee, E. Anderson, and R. Han, “X-mac: A shortpreamble mac protocol for duty-cycled wireless networks,” 4th ACMConf. on Embedded Networked Sensor Systems (SenSys), Boulder, CO,pp. 307–320, Nov. 2006.

[12] J. Polastre, J. Hill, and D. Culler, “Versatile low power media accessfor wireless sensor networks,” 2nd ACM Conf. on Embedded NetworkedSensor Systems (SenSys 2004), Baltimore, MD, pp. 95–107, Nov. 2004.

[13] “IEEE 802.15.4-2006: MAC and PHY specifications for LR-WPANs,”http://ieee802.org/15/pub/TG4.html.

[14] P. Kumar, M. Gunes, A. A. Almamou, and J. Schiller, “Real-time,bandwidth, and energy efficient IEEE 802.15.4 for medical applications,”7. GI/ITG KuVS Fachgesprach ”Drahtlose Sensornetze”, FU Berlin,Germany, September 2008.

[15] I. Joe, “A patterned preamble mac protocol for wireless sensor net-works,” IEICE Trans. Communication, vol. E91-B, no. 2, Feb. 2008.

[16] “OMNeT++,” http://www.omnetpp.org.