An energy efficient and delay sensitive centralized MAC protocol for wireless sensor networks

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aces 30 (2008) 20–31www.elsevier.com/locate/csi

Computer Standards & Interf

An energy efficient and delay sensitive centralizedMAC protocol for wireless sensor networks

Celal Ceken ⁎

Kocaeli University, Technical Education Faculty, Electronics and Computer Education Department, 41380 Kocaeli, Turkey

Received 13 February 2007; accepted 11 June 2007Available online 30 June 2007

Abstract

Energy consumption is one of the most crucial design issues in wireless sensor networks since prolonging the network lifetime depends on theefficient management of sensing node energy resource. In this research study, a new TDMA based MAC protocol, which is not only energy awarebut also delay sensitive, is introduced for wireless sensor networks. In the proposed MAC, to achieve energy conservation, sensing nodesemploying the proposed MAC sleeps periodically to reduce duty cycle and minimize idle listening. In addition, to provide lower message delay,any time critical sensing node requests extra time slots form the central node when its queue size exceeds the upper threshold value. Unlikecommon wireless sensor network models with a multi-hop topology, the proposed WSN architecture has a centralized structure especially forenergy efficiency and fulfillment of the delay requirement of time critical networking applications. The proposed MAC has been modeled andsimulated using OPNET Modeler Software for performance evaluation. Simulation results of the WSN model employing the new MAC are alsopresented including comparisons with those of a WSN counterpart employing conventional IEEE 802.11 DCF MAC protocol. By varying theinterarrival time between 1 and 8 s for 100 wireless sensing nodes, in the best case, as a consequence of the new scheduling algorithms developed9448 times better end to end message delay result and 1.9 times lower energy consumption ratio have been obtained for WSN employing theproposed MAC when compared with the WSN model employing IEEE 802.11 DCF MAC.© 2007 Elsevier B.V. All rights reserved.

Keywords: Wireless sensor network; Energy efficiency; MAC; TDMA; Latency

1. Introduction

Recent progresses in micro electronics and wirelesscommunication technologies have led to need for widespreaduse of small, mobile, low-power, low-cost, multifunctionalsensor nodes with sensing, local processing and wirelesstransmission capabilities. In a traditional sensor networksystem, to carry out a specific task, sensing nodes transmit thedata obtained from the working environment to a centralprocessing node through wired medium. These systems haverelatively less number of nodes and the sensors deployed haveno local processing power. However, the new tendency ismoving towards building distributed networks consisting ofsensing nodes small in size as well as with local processing and

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wireless transmission abilities, namely wireless sensor networks(WSNs).

Because of their ease of deployment, low cost, flexibility,and ability to self-organize, WSNs can be deployed in almostany environment, especially those where conventional wiredsensor systems are impossible, unavailable or inaccessible.Their potential applications included environmental detectionand monitoring, smart spaces, disaster prevention and relief,medical systems, home automation, scientific exploration,interactive surrounding, robotic exploration, etc. [1,2].

WSN applications have noticeably different characteristicsand requirements from traditional wireless applications. An SN(Sensing Node) in a WSN is expected to be battery equipped,and to change or recharge the power supply is usually verydifficult. Therefore energy conservation, which is essential forprolonging the lifetime of the SN and correspondingly of thenetwork, is a more crucial issue in WSNs than such otherperformance metrics utilized for traditional network systems as

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21C. Ceken / Computer Standards & Interfaces 30 (2008) 20–31

throughput and latency. Accordingly, most of the ongoingresearches about WSNs aim at providing lower energy con-sumption ratio. Like in any other wireless systems, maximumenergy is consumed by radio functions such as sending, re-ceiving, and idle listening periods in WSNs. In order to reducethe energy consumption ratio, an efficient MAC (MediumAccess Control) protocol that provides effective allocation ofmedium resources shared by many different SNs must beutilized.

The primary goal of this research study is to implement anew energy-aware TDMA (Time Division Multiple Access)based MAC protocol for WSNs. With the scheduling algorithmsdeveloped for the proposed MAC, it is intended to achieverelatively better end to end message delay results for especiallytime critical application traffics as well as to fulfill the lowerenergy consumption requirement.

In the proposed MAC, in order to reduce latency of any delaysensitive application, an extra slot is assigned to the relevantSN. Extra slot request takes place when any time critical SNqueue size exceeds the upper threshold value. The schedulingalgorithms developed to perform these functions are the majorcontribution of this study. In addition, for energy efficiency, thenon-time critical SNs put themselves into sleep modeperiodically to reduce the duration of idle listening which isthe major energy consumer. And this operation is the othercontribution of the paper.

Computer modeling and simulation of the new approach andits application for a WSN scenario are realized using OPNETModeler software. Simulation results are also presentedincluding comparisons with those of a WSN counterpartemploying classical IEEE 802.11 DCF (Distributed Coordina-tion Function) MAC protocol.

The remainder of the paper is organized as follows. In thenext section, a brief introduction on WSNs and their networkcomponents is given. Section 3 presents general informationabout the WSN MAC protocols with comparisons. It alsoprovides a detailed overview of contention based CSMA/CAMAC protocol that will be used for performance comparisons.Overall properties and design stages of the proposed MACprotocol together with related algorithms are described

Fig. 1. General architecture of

comprehensively in Section 4. Section 5 includes an exampleWSN scenario, consisting of several SNs and a central accesspoint all incorporate with the proposed MAC, which has beenmodeled and simulated under different networking conditions.The simulation results obtained are compared with those of another WSN scenario with nodes employing CSMA/CA MACprotocol that are also obtained under the same networkingconditions as former network scenario, followed by perfor-mance evaluation of both networks. The last section gives thesummary about the proposed MAC protocol with final remarks.

2. Wireless sensor network architecture

In Fig. 1, the general architecture of a wireless sensor node ispresented. As seen from the figure, commonly, a wireless sensornode is composed of four major components which are namely,the sensing unit, the processing unit, the power unit and finallythe wireless transceiver unit [2].

The sensing unit converts such measured physical quantitiesas humidity, pressure, temperature, fuel tank level, flow rate,position, velocity, acceleration, chemical concentration, etc.into a voltage signal and thereafter digitizes it to produce digitaloutput for processing. The processing unit with a microcon-troller controls all of the functions of the sensor node andmanages the communication protocols to carry out specifictasks. Communication between the SN and the network it isattached to is provided by the transceiver unit. And finally thepower unit, which is the most crucial component of a sensornode, supplies mandatory power to all of these units.

In addition to these major components, a sensor node mayalso include application depended components such as powergenerator, location finding system and mobilizer. Powergenerators, like solar cells, may be utilized to support thepower unit for prolonging the sensor node lifetime. Theapplications requiring the location information of the senseddata must be equipped with a location finding unit. Some of theWSN systems with mobility supported SNs must be providedwith a mobilizer system to tackle mobile sensing processes.

The protocol stack of SNs and the center node, gatheringsensed information from the sensor nodes, consists of

a wireless sensing node.

22 C. Ceken / Computer Standards & Interfaces 30 (2008) 20–31

application, transport, network, data link and physical layerstogether with power management, mobility management andtask management planes [2].

Since the WSN applications and their requirements varysignificantly, the architecture of the WSN and service require-ments may also be different. While the bit error rate (BER) is avital service requirement for some applications entailing apowerful error control technique, the others such as healthcareapplications may need to ensure low time delay for the packetstransferred.

In this research study presented, a new energy aware MACprotocol which is employed in data link control layer isproposed. The data link layer provides SNs with communica-tion functions to share the wireless medium efficiently as wellwith essential error control tasks. In the following sections,WSN MAC protocols and the proposed MAC technique will beexplained in detail.

3. WSN MAC protocols

As mentioned before, one of the most challenging problemsin WSN design is energy efficiency and almost all of theenduring researches about WSN subject consider this require-ment. The major energy consumers in WSNs are radiocommunication functions such as transmitting, receiving, andidle listening. To reduce energy consumption of a wireless SNan effective MAC protocol, an algorithm that defines in whichmanner the wireless medium will be shared by the nodesconstructing the network, must be utilized.

There are several studies found about WSN MAC protocolsin literature. The MAC techniques proposed for WSNs can bedivided into two categories, namely contention based andTDMA based protocols [3,4].

IEEE 802.11 DCF (Distributed Coordination Function) is acontention based MAC protocol that is mainly built on theMACAW [5], and widely employed in early WSN applications.In this study, the performance results of the new MAC protocolproposed will be compared with those of IEEE 802.11 DCF[3,4]. The frame format and timing schema of an IEEE 802.11DCF MAC is illustrated in Fig. 2.

In this technique based on CSMA/CA (Carrier SenseMultiple Access with Collision Avoidance), before datatransmission starts, the source node firstly listens the medium.

Fig. 2. Frame structure and timing schema o

If the channel is sensed “idle” for D interval then it sends a shortRTS (Request to Send) packet to the destination node informingupcoming packet transmission. When the destination nodereceives the RTS, if it is proper, after a SIFS (Short Inter FrameSpace) interval it sends a CTS (Clear to Send) reply packetallowing source node to begin transmission. After that, thepacket can be delivered to destination node. This process isrepeated for all new packet transmission requests. RTS and CTSpackets are utilized to avoid hidden terminal problem that resultin collisions. Accordingly, the possibility of packet collision canbe reduced, but can not be eliminated entirely. The performanceresults of the IEEE 802.11 DCF MAC are given in Section 5.2including comparisons with those of the proposed MAC.

A contention-based SMAC protocol is described in [3]. Forthis protocol that is based on CSMA/CA, energy conservationand self-configuration are primary goals, while per-nodefairness and latency are less important. To provide energyconservation, the SMAC protocol tries to reduce undesirableenergy depletion due to collision, overhearing, packet overheadand idle listening as well as it turns the radio on and off based onthe fixed duty cycles. The main drawback of SMAC is that theuse of fixed duty cycles can waste considerable amounts ofenergy since the communication sub-system is activated eventhough no communication will take place.

The TMAC [6], another contention based protocol, uses anadaptive duty cycle to obtain higher energy efficiency whencompared to the fixed duty cycle used in SMAC. The DSMAC[7] adds dynamic duty cycle feature to SMAC to achieve betterlatency for delay sensitive applications. In the DMAC [7]protocol, that can be considered as an improved version ofSlotted Aloha, the primary goal is not only the energyconservation but also achieving lower latency. The WiseMAC[8] protocol which combines TDMA and CSMA techniquesdetermines the length of the preamble dynamically to reduce thepower consumption and thus it results better performance underespecially variable traffic conditions. Comprehensive informa-tion on WSN MAC protocols will not be given here due tospace limitation, however, it can be found in [4,9].

4. The proposed MAC protocol

In most of the previous researches related to WSNs, the majorgoal is to minimize the energy consumption of SNs. However, the

f the IEEE 802.11 DCF MAC protocol.

Fig. 3. Frame structure and timing schema of the proposed MAC protocol.


focus of this work is not only improving the energy conservationperformance but also providing a better average packet transferdelay for especially time critical application traffics.

The energy consumption of each node in a WSN isdominated by the cost of communication, rather than compu-tation. The basic wireless functions for an SN are; receive, idle,and transmit processes. The energy consumption for thetransmit mode is calculated based on the distance of theneighbors, the transmission capacity, and the size of themessage to transmit. Measurements show that idle mode, inwhich the SN only listens the medium for possible trafficreception, consumes 50–100% of the energy required forreceiving. In [10], the ratios of idle, receive, and send processesare measured like 1, 1.05, and 1.4, respectively. Major energywasting sources determined for wireless functions of an SN are[9,3]:

• Idle listening; means listening of medium for possible dataflow. Energy consumed in idle listening dominates all othercosts.

• Collision; takes place when an SN receives more than onepacket at the same time. Collision results in discarding of thepackets and entails retransmission which boosts the energyconsumption.

• Overhearing; means an SN receives packets destined toother SNs.

• Control packet overhead; size of the control packets forcontrol signaling should be as small as possible.

• Overemitting; takes place even though the receiving node isnot ready to accept, a message is sent to destination.

A centralized TDMA based MAC protocol, which has alsobeen studied in this work, is a good solution for most of these

Fig. 4. Duty cycle of the n

problems. This work introduces a demand assignment sched-uling scheme to be utilized in the proposed WSN MACprotocol. As a property of TDMA multiplexing technique, radiospectrum is divided into time slots which are assigned todifferent SNs and an SN can send data sensed only in its owndedicated slot(s). Due to the FDD duplexing technique utilized,an SN with the proposed MAC has two distinct carrierfrequencies for uplink and downlink channels. The framestructure and timing schema of the proposed MAC protocol isshown in Fig. 3.

When an SN has data to send, it initially asks for atransmission channel, i.e. time slot, from the CN (Central Node)which coordinates the available bandwidth usage and collectsthe data sensed by SNs in its coverage area. The CN thenassigns a time slot for this connection request using a dynamicST (Scheduling Table) that is controlled with an algorithmexplained in the following sub-sections.

Furthermore, when a time critical SN needs more band-width that means the queue size exceeds the upper thresholdvalue, it asks again for extra time slot from the CN. Then, CNassigns extra slot for this SN if there is available empty slot inST. Thus, relatively better end to end delay results can beprovided for delay sensitive data traffics. This schedulingschema utilized in the proposed MAC is the major contributionof the study. Especially in the light traffic conditions,traditional wireless network nodes are in idle mode for mostof the time. However, they must listen to the channel to receivepossible data traffics. Since the energy consumption is crucialfor WSNs and the idle mode consumes considerable amountof energy, turning off the radio, if no traffic exists, is quitereasonable.

In the proposed model, it is assumed that all the SNs, exceptdelay sensitive ones, have three operational modes; transmit,

on-time critical SNs.

Fig. 5. (a) Connection request packet, (b) Connection reply packet, (c) Data packet, (d) Extra slot request packet, (e) Extra slot reply packet, (f) Release slot packet.


idle, and sleep. Since the energy consumption ratios of receiveand idle mode operations are approximately the sameaccording to the results measured in Ref. [10], the receivingfunction has been omitted and its energy consumption ratio hasbeen added to that of idle mode operation. The amount ofenergy consumed depends upon the operational modes the SNis in. Sleep mode operation is utilized to accomplish less

Fig. 6. The SN MAC la

energy consumption and in this context, all the non-timecritical SNs sleep periodically (Fig. 4).

Besides, in the proposed MAC, in order to reduce latency,time critical SNs are allowed to utilize the time slots of otherSNs when they are in sleep mode. To achieve this function, theduty cycle of non-time critical SNs are chosen periodic (i.e. nottime variant).

yer process model.

Fig. 7. The SN MAC layer process model algorithm.


The overall properties of the proposed MAC can be sum-marized as follows:

• Due to the centralized network topology and TDMAscheduling technique utilized, all the aforementioned energywest sources such as collision, overhearing, control packetoverhead, and overemitting can be decreased.

• Non-time critical SNs put themselves into sleep modeperiodically to reduce the energy consumption, whichprolongs the lifetime of the network. Besides, delaysensitive SNs are allowed to utilize the time slots of anySN that is in sleep mode, which results is lower end to endmessage delay.

• In a centralized structure, the SNs are directly connected tothe CN. Therefore, it is not necessary to execute a routingalgorithm, which results in less energy consumption andprovides lower end to end message delay.

• Time synchronization process is relatively simpler.• Self-configuration can also be achieved easily by thecontrol packets namely connection request, extra slotrequest, and release slot request.

• Finally, with the scheduling algorithm employed in theproposed MAC, effective utilization of resources such asbandwidth and energy can be satisfied. The extra time slotsdedicated for delay sensitive traffic results in relatively betterlatency performance.


On the other hand, scalability is the major drawback of heproposed model with centralized structure when compared withthe model with multi-hop topology.

The MAC protocol proposed in this research study is dividedinto two complementary parts operating at the SN and CN. Inthe following sub-sections, these parts and their simulationmodels realized using OPNET Modeler software are explainedin detail.

4.1. Wireless sensor node MAC model

The SN wireless functions of the proposed MAC protocolinclude; requesting a connection establishment, asking for extratime slot(s) for delay sensitive traffics, getting its dedicated timeslot(s), informing deallocation of extra time slot(s), and sendingdata in its own time slot(s). Besides, for non-time critical SNsthere is an extra function, namely sleep mode process in whichSNs defer their wireless operations to reduce energy consump-tion. In the WSN scenario studied, any new added SN creates acontrol packet called cc_WSN_conreq_pk (Fig. 5a) in order toinform the CN about its bandwidth requirement and transmits itin the first available empty slot. Slot number 1 in the ST, namelycontrol slot, is reserved for such control packets as connectionestablishment, extra time slot request and release slot request.When an SN requires sending a control packet, it uses the firstempty data or control slot.

When the CN gets the connection request packet it allocatesa time slot, if the resources are sufficient, for the request andsends the slot number to the related SN using the connectionreply packet (Fig. 5b). After an SN gets its time slot(s), whichmeans the connection has been established, the informationsensed is transferred by the data packet illustrated in Fig. 5c in

Fig. 8. The CN MAC la

its own time slot(s). A data packet comprises 48 bytes,consisting of a 1-byte header (SourceID), and a 47-byteinformation field for sensed data. When an SN needs morebandwidth for delay sensitive traffics, it requests extra time slotagain from the CN using extra slot request packet (Fig. 5d). Ifthere are adequate number of empty slots, CN allocates onemore time slot and sends the slot number to the related SN usingthe extra slot reply packet (Fig. 5e). Finally, the CN is informedto release extra slots allocated to time critical SNs, using releaseslot packet (Fig. 5f) when the queue size is less than the lowerthreshold value. A 2-byte error correction field (CRC) which isused for detection and correction of the possible bit errors is alsoadded to all packets traveling over the network. The processmodel of the proposed WSN MAC employed in SN and all itsfunctions are illustrated in Figs. 6 and 7, respectively.

The process starts with the big arrow, pointing the init state.This state performs a delay until the other processes in thesimulation are initialized and loads the control variables. Thenthe process enters the idle state and waits here until a specificinterrupt arrives. The conReq state machine creates connectionrequest packet, informing connection establishment, and sendsit to the CN. The reqResp state machine obtains the number oftime slot assigned by the CN. The fromSrc state machine getsthe data sensed from the upper layer, segments it into thepackets and inserts them into the queue. The data packetsreceived from the upper layer are sent to destination in the timeslot(s) dedicated to the SN in toTX state machine. The sleepstate machine, for non-time critical traffics, turns off the radiofunctions for a specific time interval to conserve energy. TheextSlotReq state machine creates extra slot request packet toinform extra bandwidth requirement for delay sensitive traffics.Extra slot release packet is created and sent to the CN in

yer process model.


releaseSlot state machine. The fromRx state machine handlesany arrived packets destined to the SN.

4.2. Central node MAC model

The CN gathers all the data sensed from the environment bythe SNs in the cluster and coordinates how the SNs will accessthe wireless medium fairly. The CN functions of the proposedMAC protocol include three main processes. These are namely;assigning time slot for any SN, delivering any arrived datapackets to upper layer and allocating/releasing extra time slotsfor delay sensitive data traffics using the ST scheduling

Fig. 9. The CN MAC layer p

algorithm. Fig. 8 shows the proposed CN MAC model realizedusing OPNET Modeler.

The scheduling algorithm operates in the CN allocatesavailable bandwidth, i.e. time slots, for the requesting SNs. Theinformation about which slots will be used by SNs is hold in atable called ST (Scheduling Table). There are three fields foreach slot in ST, which are Terminal Number, Dedicated, andPriority. The Priority field can get two values; “1” for highpriority, and “0” for low priority, and is used especially tohandle extra slot requests. When any SN asks for an extra slotfrom the CN, the scheduling algorithm assigns an empty slot forit and set the Priority field to “0”. The slot whose Priority field is

rocess model algorithm.


“0” may be reassigned for a new connection request, in caseempty slot does not exist.

The process starts with the init state, then enters the idlestate and waits here until a specific interrupt arrives. ThefromRx state machine delivers any arriving packet to the nextstate machine considering its format. The bwRequest statemachine handles connection requests and allocation/deal-location extra time slot requests, and also executes a fairscheduling algorithm that manages the ST. The data statemachine delivers the sensed information to upper layer toexecute the specific task. The CN MAC layer process modelalgorithm is outlined in Fig. 9.

5. Computer simulation of WSN

5.1. Assumptions

In the example scenario, shown in Fig. 10, in order togenerate sensed data traffics there are numerous SNs which are

Fig. 10. Example W

deployed randomly and equipped with the proposed MACprotocol explained in the previous section. The sensed datatraffic introduced to the network by any SN is destined to theCN, which is the sink node where the results of sensormeasurements are collected, for executing a specific task. It isassumed that some of these nodes are generating delay sensitiveapplication traffics while the others are generating non-timecritical data traffics. Diameter of the cluster which constructs thenetwork topology has been chosen 100 m.

In the simulation environment a free space channel propaga-tion model that supports to predict received signal strength whenthe transmitter and receiver have a clear, unobstructed line-of-sight path between them is utilized. The packet loss ratio metric isnot considered here since the buffers are assumed to have enoughcapacity so that no data packet is lost due to buffer overflow.Moreover, it is also assumed that the CRC bits added to thepackets avoids the possible bit errors.

Another WSN model analogous to the one above except thatIEEE 802.11 DCF MAC protocol is utilized instead of the

ATM scenario.

Table 1Simulation parameters

Parameters Value

Message size 20 packets×50 a BytesInterarrival time 1 a–10 a sData rate 1 Mb/sFrequency band Uplink = 3 GHz and Downlink = 4 GHzTransmitter power CS = 10 mW and SNs = 10 mWModulation schema BPSKNumber of SNs 100Queue threshold values 12,000–9000 bitsArea size 100 m×100 mChannel model Free space propagation model (LoS)

a Generated using exponential distribution function exp (mean).


proposed MAC has also been simulated using OPNETModeler.Working conditions of both network models have been chosensimilar for consistent performance comparisons.

5.2. Simulation results and discussion

In the proposed MAC, an uplink frame consists of 220 timeslots each has 1 ms length and contains 2 data packets. Thesimulation parameters are given in Table 1.

Simulation results of the both WSN models described aboveare presented under varying network load conditions followedby performance analysis and comparisons. The simulation wasrun for 3600 s.

In the example scenario, all non-time critical SNs putthemselves into sleep mode after 50 s of being idle and stay thismode for next 50 s, and this process repeats throughout thesimulation run time. Varying the message size of all SNsapplication traffics, power consumption and average EED (end-to-end delay) results of the delay sensitive traffic transferbetween SN1 and CN, of non-time critical traffic transferbetween SN2 and CN have been collected during the simulationrun time for both WSN models.

In the proposed MAC, there are two factors that impact thepower consumption and latency performance of the SNs. The

Fig. 11. Average EED results

first is the sleep mode operation, for non-time critical SNs, inwhich the power consumption ratio is considerably reducedwhile it results in increasing end to end message delay. Thesecond is the extra slot usage for delay sensitive SNs, whichprovides lower latency performance but conversely results inhigher power consumption ratio due to the increasing channelutilization.

In Fig. 11, average EED results of the WSN models arepresented as a function of the interarrival time. For heavytraffics (i.e. interarrival time is up to 3 s), in the best case, thedelay sensitive application traffic (i.e. between SN1 and CN)experiences approximately 9448 times lower (by virtue of extraslot utilization and demand assignment scheduling algorithm),and the non-time critic application traffic (i.e. between SN2 andCN) experiences approximately 271 times lower averagemessage delays in the proposed MAC based WSN modelwhen compared with those of the IEEE 802.11 DCF MACbased WSN model.

However, for the light traffics (i.e. interarrival time isbetween 3 s and 8 s) EED results of IEEE 802.11 DCFMAC aregenerally better than those of the both proposed MAC models.Moreover, it can also be observed from the figure that, for theproposed MAC, the longer duty cycle (in the scenario, SN1 hasa longer duty cycle than SN2 has, as a consequence of sleepmode operation), results in a decrease in message delay asexpected.

In Fig. 12, measured average power consumption results ofthe WSN models are presented as a function of the interarrivaltime. As can be seen from the figure, power consumption resultsof the proposed MAC are better than those of the IEEE 802.11DCF MAC for all traffic conditions. In the best case, non-timecritical SN2 equipped with the proposed MAC consumes 1.8times lower energy than the one employing the IEEE 802.11DCF MAC.

For the proposed MAC model, non-time critical SN2provides 1.1−1.8 times lower power consumption than SN1does. This is not a surprising outcome since SN1 uses extraslot(s) to accomplish better latency performance. Accordingly,

of the MAC protocols.

Fig. 12. Average power consumption results of the MAC protocols.


it results in increasing channel utilization that boosts energydissipation. Besides, SN2 puts itself into the sleep modeperiodically and this provides aforementioned significantamount of reduction in power consumption. IEEE DCFMAC based SNs consume more energy than SNs employingthe proposed MAC for all load conditions as can be seen fromthe figure.

For the network model employing the proposed MAC, whenan SN enters in sleep mode to save energy, its wireless functionssuch as transmit, receive, and idle are halted. During this period,all the data sensed are stored in the buffer. In Fig. 13, queuingstatuses of SN1 and SN2 are shown. As can be seen from the

Fig. 13. Queuing statuses of SN1 an

figure, size of the data in the SN2 queue is more than that ofSN1 queue for the duration of the simulation run time as aconsequence of sleep mode operation. The SN2 turns off radiofunctions periodically, provides lower energy dissipation, andconversely results in increasing message transfer delay asexplained before.

In Fig. 14 that stands to reveal the effect of extra slot usage,queuing statuses of SN1 both with extra slot and without extraslot are shown. Any time critical SN asks for extra slot from theCN when its queue size exceeds the upper threshold value. Aftera new time slot assigned for the SN, accordingly, its queuesize decreases below to the upper threshold value until the

d SN2 with the proposed MAC.

Fig. 14. Queuing statuses of SN1 and SN2 with the proposed MAC.


simulation end as can be seen from the figure. It is obvious thatthe queue status of SNs impacts the end to end message delay,namely the lower queue size result in the lower end to endmessage delay as can be seen in Fig. 11.

6. Conclusions

Many ongoing researches on WSN subject focus only on theenergy efficiency. In this study a new energy aware and delaysensitive MAC protocol for WSNs has been proposed andsimulated using OPNET Modeler software. In the proposedMAC, in order to reduce latency of any delay sensitive appli-cation, an extra slot is assigned to the relevant SN when its queuesize exceeds the upper threshold value. The schedulingalgorithms developed to perform these functions are the majorcontribution of this study. In addition, for energy efficiency, thenon-time critical SNs put themselves into sleepmode periodicallyto reduce the duration of idle listening which is the major energyconsumer. This operation is the other contribution of the paper.

The simulation results have been compared with those ofthe IEEE 802.11 DCF MAC protocol. According to theperformance results obtained, with the scheduling algorithmsdeveloped for the proposed MAC protocol, not only havelower energy consumption ratios been fulfilled but also lowerend to end message delay results have been achieved forespecially delay sensitive data traffics. For the proposed MAC,in the best case, 1.9 times lower energy consumption resultsand 9448 times lower latency performance have been obtainedwhen compared with those of IEEE 802.11 DCF MACprotocol.

Acknowledgement

The author would like to thank Assoc. Prof. Dr. Ismail Erturkfor his invaluable contributions to this study.

References

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Celal Ceken received the M.Sc. and PhD degreesfrom Kocaeli University, Turkey in 2001 and 2004,respectively. His active research interests includewireless communications, broadband networks,WATM, QoS, high-speed communication protocols,and wireless sensor networks.

An energy efficient and delay sensitive centralized MAC protocol for wireless sensor networks

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