Mobile Networks and Applications 10, 627–637, 2005C© 2005 Springer Science + Business Media, Inc. Manufactured in The Netherlands.

SYN-MAC: A Distributed Medium Access Control Protocolfor Synchronized Wireless Networks*

HONGYI WU, ANANT UTGIKAR and NIAN-FENG TZENGThe Center for Advanced Computer Studies, University of Louisiana at Lafayette, P.O. Box 44330, Lafayette, LA 70504-4330

Abstract. In this paper, we propose a novel medium access control (MAC) protocol, called SYN-MAC (for SYNchronized MAC), basedon a binary countdown approach tailored for wireless networks. SYN-MAC has several attractive features such as simplicity, robustness,high efficiency, fairness, and quality of service capability. We evaluate SYN-MAC in terms of collision probability, system throughput, andpacket delay, via both analysis and simulation. Our results show that, with properly chosen parameters, SYN-MAC can achieve a very lowcollision probability, packet delay tolerance, and extremely high channel efficiency (of >90%) under a wide range of traffic load. As a result,SYN-MAC may serve as an alternative to IEEE 802.11 for the wireless stations in synchronized networks.

Keywords: binary countdown, fairness, IEEE 802.11, medium access control (MAC), SYN-MAC

1. Introduction

With unmatched flexibility to support the communication ofmobile users, the wireless local area networks (WLANs) andthe mobile ad hoc networks have become increasingly pop-ular over the past few years. Though developed as indepen-dent networking technologies, the WLAN and the mobile adhoc network are envisioned to be integrated into other exist-ing networks, e.g., the cellular system, the satellite system,and/or the Internet, serving as a cost-effective complement tothe fixed infrastructure. Several integrated systems involvingthe cellular and the ad hoc technologies have been proposedin [14,23,25], where each mobile station can communicatewith both the cellular system and the ad hoc network (orthe WLAN). In addition, more and more mobile devices areequipped with the GPS (global positioning system) receivers,giving rise to a loosely integrated ad hoc and satellite system.The infrastructure of the integrated networks can provide ef-fective support (e.g., synchronization, signaling, authentica-tion, etc.) to the mobile stations in the ad hoc networks orthe WLANs, dramatically enhancing system performance. Inparticular, the mobile stations can reach system-wide synchro-nization by detecting the pilot signals in the cellular systemsand/or the GPS signals from the satellites, without consumingadditional resources (e.g., the bandwidth of cellular/satellitechannels). Other synchronization schemes recently proposedfor multi-hop wireless networks may also be employed [21].In this work, we investigate the potential performance im-provement of wireless networks with such synchronization.Specifically, we propose and evaluate a novel medium access

* This work is supported in part by National Science Foundation CAREERAward under Award Number CNS-0347686, by U.S. Department of Energy(DoE) under Award Number DE-FG02-04ER46136, and by Board of Re-gents, State of Louisiana under Contract Number No. DOE/LEQSF(2004-07)-ULL and LEQSF(2003-06)-RD-A-37. Part of this work was presentedin the student poster session of IEEE International Conference on NetworkProtocols (ICNP) 2003, Atlanta, GA.

control (MAC) protocol based on an enhanced binary count-down scheme for synchronized wireless networks.

The MAC protocol resolves contention for accessingto the shared medium. As a key design issue of wirelesscommunication, various MAC protocols have evolved overthe years for different networks. In the cellular system,centrally-controlled contention-free schemes, such as FDMA(frequency division multiple access), TDMA (time divisionmultiple access), or CDMA (code division multiple access),are usually adopted for the data channels, while randomaccess is employed in the uplink control channel [9]. Whenan access point is present, the WLAN may use a pollingscheme as defined in IEEE 802.11 PCF (point coordinationfunction) [10] to provide contention-free and QoS (quality ofservice)-guaranteed service. In a wireless network involvingmultiple hops (i.e., where two stations may not communicatewith each other directly), efficient and distributed multipleaccess control is especially important. Several asynchronousand distributed MAC protocols have been considered in thelast several decades. In particular, the carrier sense multipleaccess with collision avoidance (CSMA/CA) scheme hasbeen standardized in IEEE 802.11 DCF (distributed coordi-nation function) [10] and widely implemented in WLANsand ad hoc networks. On the other hand, synchronized anddistributed approaches able to potentially achieve higherperformance, however, have not been adequately studied yet,since the multi-hop wireless network (e.g., the mobile ad hocnetwork) was originally designed as an independent systemwith no provision to obtain system-wide synchronization.

In this paper, we propose a SYN-MAC (short for Synchro-nized MAC) protocol, based on an enhanced binary count-down scheme that solves the unfairness problem and the hid-den station problem brought up earlier in [28]. SYN-MAChas several attractive features such as simplicity, robustness,high efficiency, fairness, and QoS capability. We evaluateSYN-MAC in terms of collision probability, system through-put, and packet delay, via both analysis and simulation. Our

628 WU ET AL.

results show that SYN-MAC achieves significantly betterperformance compared with existing protocols. With properlychosen system parameters (e.g., the length of the contentionintervals as to be discussed in Section 3), SYN-MAC can reacha very low collision probability, packet delay tolerance, andextremely high channel efficiency (of >90%) under a widerange of traffic load, outperforming ADHOC MAC (a recentlyproposed MAC protocol for synchronized wireless networks),whose maximum channel efficiency is only 75% [4].

The rest of this paper is organized as follows. In Section 2,we discuss related work. In Section 3, we introduce the pro-posed SYN-MAC protocol. The analytic and simulation re-sults are presented in Section 4. Finally, Section 5 concludesthe paper.

2. Related work

Various MAC protocols have been proposed for wireless net-works. They can be classified into two categories, namely,non-synchronized protocols and synchronized protocols. Theformer does not need system-wide time synchronization,while the latter does.

Channel contention in the non-synchronized approachescan be resolved by either in-band (i.e., single channel) con-trol handshaking or out-band (i.e., multi-channel) signal-ing. Several single-channel non-synchronized wireless MACprotocols have been proposed, such as Multiple Accesswith Collision Avoidance (MACA) [12], MACA for Wire-less (MACAW) [3], and Floor Acquisition Multiple Access(FAMA) [8]. The central idea is to use the Request To Send(RTS)/Clear To Send (CTS) mechanism to solve the hiddenstation problem in wireless networks. Various approacheshave been considered to improve the performance of theRTS/CTS scheme by using power control [11,15], directionalantennas [2,5,13], etc. The RTS/CTS scheme has also beenstandardized in IEEE 802.11 Distributed Coordination Func-tion (DCF) [10]. On the other hand, several MAC protocolsbased on out-band signaling have been proposed. For exam-ple, [6,20,26] use busy tone(s) to avoid collision and eliminatethe hidden stations. Nasipuri et al. [18] introduces a multi-channel carrier sense multiple access (CSMA) protocol, whichdivides the total available bandwidth into N narrow-bandsub-channels, and then apply CSMA in each sub-channel.In [16,17,22,24], the total available bandwidth is divided intotwo or more channels, with one channel used for control andthe rest of them for data transmission.

The synchronized approaches can be further classified intotwo sub-categories, i.e., the centralized protocols and thedistributed protocols. The centralized protocols include theFDMA, TDMA, and CDMA approaches for cellular systemsand the polling scheme defined in IEEE 802.11 standard [10]and HIPERLAN [7]. While the centralized approaches per-form well in a single-hop wireless system, where the basestation (or access point) can communicate with all wirelessterminals directly, it is technically difficult and inefficient toapply them to a multi-hop wireless network without a centralcoordinator.

On the other hand, several synchronized but distributed ap-proaches [4,28] have been proposed recently. Borgonovo et al.[4] introduces an MAC architecture, called ADHOC MAC,for mobile ad hoc networks. It deploys a reliable reservationALOHA (RR-ALOHA) protocol to establish slotted/framedwireless channels. Each station can transmit in one or sev-eral slots in a frame. In a slot, the station sends not only databut also Frame Information (FI) that reports the frame statusas perceived by the terminal (i.e., which station transmits inwhich slot). Upon collecting FIs from its neighbors, a new sta-tion has the frame status within two hops and thus can choosean appropriate slot to transmit. ADHOC MAC is a distributedapproach, providing flexible and reliable medium access. Asdiscussed in [4], however, the overhead of this protocol isvery high, because each station has to send the FIs. In fact, themaximum channel efficiency of ADHOC MAC is only 75%as reported in [4].

A CSMA/CP (Carrier Sense Multiple Access with Col-lision Prevention) protocol is proposed in [28]. The authorsconsidered the use of binary countdown to resolve mediumaccess contention. The basic idea of binary countdown liesin selecting the winner based on a k-bit binary number. Onegives up contention as soon seeing a higher number. Givenfour numbers 0010, 0100, 1001, and 1010 for instance, thefirst two competitors will give up after comparing the first(highest) bit, and the third competitor gives up after the thirdbit. Finally, 1010 wins the contention. Binary countdown is awell known approach that has many applications. For exam-ple, it has been discussed in [19] as a MAC protocol, where theunique station addresses are used for contention, leading to acollision-free medium access. At the same time, however, it re-sults in unfairness among the stations because the station witha larger address always has higher priority. In [28], the basicbinary countdown scheme is used on a control channel. Afterwinning the channel access, the RT S/CT S scheme is used todeal with the hidden station problem. Further improvementand QoS support can be achieved using better binary numberassignment approaches. However, the following problem inbinary countdown itself needs to be considered in order toattain higher efficiency in a multi-hop wireless network. Let’sconsider a special case, where two nodes A and C are trying tosend data to another node, B. Assume nodes A and C are notwithin the transmission range of each other (and there are noother competitors), then no matter which binary numbers arechosen for contention, both A and C will win the channel ac-cess. Consequently, nodes A and C will simultaneously sendout RT S to B, which, however, cannot receive the RT S cor-rectly because of collision. As a result, no one may transmitduring this slot, and bandwidth is completely wasted. In fact,there is a very high probability for such a problem to happenin ad hoc networks. In a wireless LAN with an access point,the probability is even higher (e.g., let B be the access point).One solution for this problem is to employ a random back-off scheme before sending out RT S. This, however, resultsin lower channel efficiency. In the next section, we propose anovel approach in order to avoid such collision at the receiverwithout sacrificing bandwidth utilization.

A DISTRIBUTED MEDIUM ACCESS CONTROL PROTOCOL FOR SYNCHRONIZED WIRELESS NETWORKS 629

Figure 1. Frame format of the proposed MAC protocol, where CS stands for Contention Signal, HCM stands for Hidden station Clear Message, and ACKstands for Acknowledgement.

3. Proposed SYN-MAC protocol

In this section, we introduce the proposed SYN-MAC pro-tocol for synchronized mobile ad hoc networks or wirelessLANs. We first describe the proposed protocol, then presenta correctness proof, followed by the worst case analysis andfurther discussion.

3.1. Protocol description

As discussed earlier in Section 1, time synchronization can beobtained from the cellular infrastructure or from the satellitewhen a GPS receiver is available. In the proposed SYN-MACprotocol, the network-wide synchronized frames are used bythe mobile stations. As depicted in figure 1, a frame consistsof three intervals: the contention interval, the hidden stationelimination interval, and the data interval. The contention in-terval is used to resolve contention. It consists of k contentionslots. Each contention slot, say contention slot i , includes theturnaround time between the transmitting and receiving modesand the time to send a very short message, called the contentionsignal (and denoted as C Si ). The hidden station eliminationinterval is for solving the hidden station problem. A Hiddenstation Clear Message (HCM) is transmitted by the receiverduring this interval. Finally, data and acknowledgment are sentin the data interval. The parameters, such as interval lengthand slot length, are to be discussed later in Section 4.1.

The proposed medium access control scheme includesthree major steps: contention resolution, hidden station elim-ination, and data transmission, as described next.

3.1.1. Step 1: Contention resolutionA binary countdown approach is adopted to resolve con-tention. A station (say, X ) that has data to send generatesa random number with k bits, i.e., {bi | 1 ≤ i ≤ k}, where kis the number of contention slots in a contention interval. Ifbi = 1, station X sends a short message C Si in contention sloti , which contains the destination’s MAC address. Otherwise,if bi = 0, station X listens to the channel. If the channel isbusy (i.e., one or several other stations are transmitting), sta-tion X stops further transmission and gives up its attempt ofgaining access to the channel in this frame. If each station ina collision domain (i.e., an area where all stations can hearfrom each other) generates a distinct random number, onlyone station that survives at the end of the contention intervalmoves to Step 2 and continues to transmit. If two or more sta-

tions generate an identical random number that is the largestamong all numbers generated, collision may happen. As tobe discussed later in Section 4.1, however, we can choose klarge enough to keep the collision probability satisfactorilylow.

A station Y that is not a sender determines whether it isan intended receiver by checking the first received contentionsignal. If multiple stations are transmitting simultaneously ina contention slot, Y cannot receive a valid contention signaland thus wait for the next contention slot. When there is ex-actly one station transmitting in a contention slot, say sloti , station Y can receive a valid C Si and marks itself as areceiver if C Si carries its MAC address. At the same time,station Y generates a random number mask, which is a k-bitstring with the i-th bit being 1 and all other bits being 0. Aftermarking itself as a receiver, station Y ignores the followingcontention slots in this contention interval. Otherwise, if sta-tion Y receives a contention signal that contains another sta-tion’s address, Y gives up its attempt to be a potential receiverand ignores the remaining contention slots in this contentioninterval.

An example of contention resolution is illustrated infigure 2. Consider a network that includes eleven stations,labelled from A to K . Two stations are connected by a linkin the graph if they are within the transmission range of eachother. Assume stations B, C , H , and G have data to send tostations E , F , G, and F , respectively. Note that due to thelimited transmission range of wireless interfaces, not all ofthe four stations are competing with each other. For example,station B only competes with station C ; station C competeswith stations B and H ; station H competes with stations Cand G; station G competes with station H only. Each of thefour stations generates a random number as shown in figure 2(starting from the highest bit). After the first contention slot,station B gives up because it detects the transmission fromstation C . Similarly, station H gives up after the third con-tention slot. By the end of the contention interval, stations Cand G survive and are ready to enter Step 2. At the same time,node F marks itself as a receiver, as it receives the contentionsignal from station C in the last contention slot. Note that,although stations E and G are the intended destinations ofstations B and H , they do not mark themselves as receiversbecause they cannot receive valid contention signals from B(that has given up its transmission since the first contentionslot) and H (that always transmits contention signals whennode G is also in transmission mode), respectively.

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Figure 2. An example of contention resolution. The shaded nodes are the winner after Step 1. The nodes with underlines mark themselves as receivers.

3.1.2. Step 2: Hidden station eliminationAfter Step 1, only one station in a collision domain (i.e., nomore than one adjacent stations) can survive, unless identi-cal random numbers are generated. However, the hidden sta-tion problem in multi-hop wireless networks has not beenaddressed yet. For instance, since stations C and G cannotreceive the contention signals from each other, both of themconsider themselves as the winner after Step 1, and thus col-lision might occur during the data transmission interval. Notethat, however, since station F receives the contention signalsfrom both stations C and G, it can recognize the real win-ner (i.e., the one with a higher random number). In fact, inthe above example, F has generated a random number mask00000001 in Step 1, upon receiving the contention signalfrom station C in the last contention slot. In order to elim-inate potential hidden stations, a station that has marked itselfas a receiver in Step 1 sends a Hidden station Clear Mes-sage (HCM), which contains its random number mask. If asender receives the HCM correctly, it computes the bitwiseAND of the random number mask and the random numbergenerated by itself. If the result is nonzero, it can proceedto Step 3. Otherwise, the station considers itself as a hiddenstation and gives up its attempt to access the channel in thisframe.

3.1.3. Step 3: Data transmissionIn the last step, the sender transmits data, while the receiverresponds with an acknowledgement if the received data iscorrect, in the data interval. All other nodes (including somenodes marked as receivers in Step 1) cannot send or receivedata in this frame.

The protocol flow diagrams for the sender and the receiverare depicted in figure 3, which is self-explanatory.

3.2. Protocol correctness

In this subsection, we deal with the correctness of the proposedprotocol. More specifically, we prove that (1) there is no hid-den station problem in the proposed protocol, and (2) if noduplicated random numbers are generated, at least one stationcan transmit successfully. The proof is outlined by discussingthe following three cases.

Figure 3. (a) Flow diagram for the sender. B: channel is busy; M : randomnumber mask matches the random number generated by the sender. (b) Flowdiagram for the receiver. A: destination MAC address matches the receiver’s

MAC address.

Case 1: a receiver, say R, is in the transmission range of onlyone sender S. In this case, R will mark itself as a receiver whenreceiving the first contention signal from S, and send back theHCM message. Clearly, there is no hidden station problem for

A DISTRIBUTED MEDIUM ACCESS CONTROL PROTOCOL FOR SYNCHRONIZED WIRELESS NETWORKS 631

R (because there are no other senders nearby). If S generatesa higher random number than its neighbors, it wins the rightof transmission and sends the data to R. Otherwise, R willnot receive any data (but another sender that has generatedthe largest random number will transmit).

Case 2: the receiver R is in the transmission range of morethan one senders, but R is the intended receiver of only onesender S. In this case, (1) if S generates a larger randomnumber than those of all other senders, R marks itself as thereceiver upon getting a valid contention signal from S andsends the HCM message. Upon receiving HCM, S will sendthe data to R. At the same time, the HCM message blocksother nearby senders from transmitting data. Thus, there is nohidden station problem for R. (2) Otherwise, if the randomnumber generated by S is equal to or smaller than any othersender’s random number, R neither marks itself as a receivernor sends the HCM message. As a result, S will not senddata. But another sender which generates the largest randomnumber will succeed.

Case 3: the receiver R is in the transmission range of morethan one sender, and R is the intended receiver of more thanone sender. Similar to Case 2.

3.3. Further discussions

In this subsection, we analyze the worst case performance anddiscuss several unique features of the proposed SYN-MACprotocol.

3.3.1. Worst case analysisClearly, if all senders generate the same random number, nostation can transmit data successfully. But as to be discussedin Section 4.1, one may choose proper k to keep the collisionprobability sufficiently low. In the following discussion, weassume all senders generate different random numbers, andinvestigate the inherent worst case when applying SYN-MACto multi-hop wireless networks.

Intuitively, the performance bottleneck of SYN-MACseems to be at Step 1, where the senders compete for channelaccess. In particular, the worst case might occur if the stationsgenerate the random numbers with a non-increasing orderfrom left to right (or vice versa), e.g., as shown in figure 4(a),where the station identification (ID) numbers are at bottom

Figure 4. Worst case analysis, where (a) all stations are sender; (b) stations2, 4, 6, and 8 are senders, and stations 1, 3, 5, and 7 are receivers.

and the random numbers generated by the stations are at top.In contrast to our intuition, however, Step 1 of SYN-MACperforms very well in this case. More specifically, after thefirst contention slot, only station 4 gives up (assuming to startfrom the highest bit); after the second contention slot, stations2 and 6 give up; after the third contention slot, station 7 givesup. As a result, stations 1, 3, 5, and 8 survive after Step 1.1

Since the adjacent stations cannot transmit simultaneously,the best scenario is to have four survival stations, as achievedin this case.

In fact, the real bottleneck is at Step 2, due to the receivers.For example, in a network illustrated in figure 4(b), let sta-tions 1, 3, 5, and 7 be the intended receivers of stations 2, 4,6, and 8, respectively. After Step 1, all senders (i.e., stations2, 4, 6, and 8) survive, and all receivers (i.e., stations 1, 3, 5,and 7) mark themselves as receivers. But when the receiverssend HCM messages to the senders, a collision occurs at eachsender except station 8. Consequently, only station 8 can senddata.2 This worst case results from the use of a distributed ap-proach. Similar situations also appear in distributed schemeslike HIPERLAN or IEEE 802.11.

3.3.2. Main features of SYN-MACThe proposed SYN-MAC protocol has several unique featuresdiscussed as follows.

(a) Simplicity. The implementation of SYN-MAC is simple.Compared with IEEE 802.11, SYN-MAC needs neithercarrier sensing before transmission nor Network Alloca-tion Vector (NAV) maintenance/updates. Since contentioncan be effectively relieved in Step 1, the back-off mech-anism is unnecessary. This simple design results in sig-nificantly reduced computational complexity, memory re-quirement, and energy consumption.

(b) High efficiency. High throughput is achieved by choosingan appropriate k value as will be discussed in Section 4.1,so that the collision probability (due to two or more sta-tions choosing the same largest random number) is suffi-ciently low, while the overhead of the contention intervalis small. In addition, SYN-MAC exhibits no bandwidthwaste during back-off (unlike that in IEEE 802.11), fur-ther improving its efficiency.

(c) Fairness. Since every node generates a random number foreach channel access attempt, no stations have unwantedpriority over other stations. More over, the unfairnessproblem reported in [27] due to the back-off scheme ofIEEE 802.11 DCF (which favors the sender of last suc-cessful transmission) does not exist in SYN-MAC.

(d) Robustness. The protocol is highly robust as long asthe synchronization can be maintained. Since channel

1 This only shows that Step 1 is not the bottleneck. It does not imply thatall senders (i.e., stations 1, 3, 5, and 8) can finish the data transmissionsuccessfully.

2 Note that station 8 can finish a successful transmission even in a networkwith a circular topology, where station 8 has two neighbors, stations 1 and7.

632 WU ET AL.

Figure 5. Random number blocks for different QoS classes.

contention starts all over again after each frame, any prob-lem (e.g., the collisions), if arising, is temporarily for oneframe only.

(e) Decentralization. SYN-MAC is a distributed approach.Each station generates the random number by itself forchannel contention. No central controller or infrastructuresupport is needed.

(f) QoS support. The QoS support of our protocol can beefficiently achieved by dividing the random numbers intoseveral blocks (see figure 5), one for each QoS class. Whena station has data in class i to be sent, it generates a ran-dom number within block i to compete for the channel.The data with a higher QoS class has higher priority andwill eliminate those channel access attempts with lowerpriority. In the same QoS class, the stations have an equalprobability of access to the channel.

Like other time-frame based approaches, SYN-MAC isless flexible than the non-synchronized schemes (e.g., IEEE802.11 DCF). In particular, if the data packet size is smallerthan the DATA field in the frame, some bandwidth is wasted.This problem can be alleviated by accumulating and aggre-gating traffic, avoiding to send single small datagrams.

4. Performance evaluation

In this section, we evaluate the performance of SYN-MACin terms of system throughput, packet delay, and collisionprobability. We first discuss an analytic model for a singlecollision domain. Then, we present the simulation results forgeneral scenarios.

4.1. Analytical study

As we discussed earlier, a contention slot includes the trans-mitting/receiving turnaround time and the time to send thecontention signal (C Si ). With the Direct Sequence SpreadSpectrum (DSSS) physical layer, the transmitting/receivingturnaround time (lT ) is less than 5 µs, and the physical layerconvergence protocol (PLCP) header has a length of 48 bits.

The contention signal contains a 48-bit receiver’s MAC ad-dress. Assume the bandwidth is M Mbps, the total length ofa contention slot lc is no longer than 5 + (48 + 48)/Mµs.HCM contains the k-bit random number mask only, with alength of lHCM = (k + 48)/M µs. The data and ACK mes-sages have a similar format as the frame defined in IEEE802.11, but without the “duration” field in the header. Morespecifically, each ACK message has 12 bytes, or equiva-lently lACK = (12 × 8 + 48)/M µs. Data message is as-sumed to be 2342 bytes by default, leading to ld = (2342 ×8 + 48)/M µs.

The number of contention slots (k) in the contention in-terval determines the collision probability. Assume there aren active stations in a collision domain (i.e., n stations withinthe transmission range of each other have data to send). Eachstation has a probability of 1/2k to choose a particular ran-dom number between 0 and 2k − 1. Note that collision occursonly if two or more stations choose the same largest randomnumber, which again ranges from 0 to 2k − 1. We examineall possible cases as follows. The probability that exactly onestation chooses 2k − 1 as its random number (i.e., one stationchooses 2k − 1, while the remaining stations don’t choose2k − 1) is

n

(1

2k

)(1 − 1

2k

)n−1

.

Similarly, we can derive the probability that exactly one stationchooses j (0 ≤ j ≤ 2 k −1) as its random number and no otherstations choose a random number greater than or equal to j ,

n

(1

2k

)(1 − 2k − j

2k

)n−1

.

Therefore, the probability that collision does not occur is

Pnk =

2k−1∑j=0

n

(1

2k

)(1 − 2k − j

2k

)n−1

. (1)

Accordingly, the average throughput in one collision domainequals

Snk = ld

l× Pn

k , (2)

where l = lC + lH + lD with lC = klc, lH = lHCM + lT , andlD = ld + lACK + 2lT .

We can also derive the average delay for a data packet,which is defined as the duration from the time when the data isready for transmission to the time when the data is actually sentout. Assume a given station has data to send, the probabilitythat it wins channel access at the m-th attempt (and has failedat the first m − 1 attempts) is

Pnk (m) =

(2k−1∑j=0

(1

2k

)(1 − 2k − j

2k

)n−1)

×(

1 −2k−1∑j=0

(1

2k

)(1 − 2k − j

2k

)n−1)m−1

.

A DISTRIBUTED MEDIUM ACCESS CONTROL PROTOCOL FOR SYNCHRONIZED WIRELESS NETWORKS 633

0 5 10 15 20 25 30 35 40 45 500.65

0.7

0.75

0.8

0.85

0.9

0.95

1

Number of active stations (n)

Col

lisio

n fr

ee p

roba

bilit

y in

one

col

lisio

n do

mai

n

k=12k=10k=8k=6

Figure 6. Analyzed collision-free probability.

Thus, the average delay is expressed by

Dnk = lC + lH +

∞∑i=1

(i − 1) × l × Pnk (i). (3)

Assuming the available bandwidth to be M = 11 Mbps andplugging in the typical values discussed earlier, we get the re-sults as shown in figures 6–8. When a small number of stationsare active, contention is low, and thus the collision probabilityis low, the throughput is high, and the delay is low. With theincrease of n, the collision probability and the delay increaseaccordingly. As can be observed, there is a tradeoff whenchoosing an appropriate k. With larger k, a lower collisionprobability can be achieved. But at the same time, large k alsoresults in higher overhead, possibly leading to lower through-put and longer delay. In the protocol implementation, k = 10can be chosen as the default value, with which the protocolcan achieve above 90% channel efficiency and acceptable de-

0 5 10 15 20 25 30 35 40 45 506.5

7

7.5

8

8.5

9

9.5

10

10.5

Number of active stations (n)

Thr

ough

put i

n on

e co

llisi

on d

omai

n (M

bps)

k=12k=10k=8k=6

Figure 7. Analyzed throughput.

0 5 10 15 20 25 30 35 40 45 500

20

40

60

80

100

120

140

Number of active stations (n)

Del

ay (

ms)

k=6k=8k=10k=12

Figure 8. Analyzed delay.

lay for a wide range of the number of stations (from 1 to 50)in one collision domain. figure 9 shows the impact of framepayload size. Clearly, the larger the datagram, the higher thechannel efficiency. This indicates that reasonably large frameshall be used in SYN-MAC, and the stations may accumulateoutgoing data in order to reduce wasted frame payload space.

4.2. Simulation evaluation

To verify our analytic model and obtain results for generalmulti-hop networks, we have implemented the proposed SYN-MAC protocol by using PARSEC [1]. Similar to those param-eters adopted in analysis, the maximum data frame size is 2342bytes and an ACK frame has 12 bytes. Channel bandwidth is11 Mbps. DSSS is employed in physical layer, with 8-chipcomplementary code keying modulation. We assume perfect

1 2 3 4 5 6 7 8 9 104

5

6

7

8

9

10

Payroll size (× 256 bytes)

Thr

ough

put i

n on

e co

llisi

on d

omai

n (M

bps)

k=12k=10k=8k=6

Figure 9. The impact of frame size.

634 WU ET AL.

10 15 20 25 30 35 40 45 508.2

8.4

8.6

8.8

9

9.2

9.4

9.6

9.8

10

10.2

Number of Active Nodes (n)

Thr

ough

put (

Mbp

s)

k=6 k=8 k=10k=12

Figure 10. Throughput in a collision domain (simu.).

10 15 20 25 30 35 40 45 500

20

40

60

80

100

120

Number of Active Nodes (n)

Ave

rage

del

ay (

ms)

k=6k=8k=10k=12

Figure 11. Delay in a collision domain (simulation).

channel condition, resulting in very low bit error rate. Thetransmitting/receiving turnaround time equals 5 µs.3 48-bitMAC address is used to identify each node in this simula-tion. Shorter identifiers (e.g., the lower 16 bits of the MACaddress), however, may be employed to reduce overhead andimprove system performance. We assume that the stations al-ways have data ready to send. Several scenarios are simulatedwith variable numbers of nodes (from 10 to 625), differentnodal transmission ranges, and a range of contention slots(4 ≤ k ≤ 12).

Figures 10 and 11 demonstrate the throughput and the de-lay performance of a network in one collision domain. Ascan be seen, the simulation results closely match our analyticmodel presented in Section 4.1. When k is small (e.g., k = 6),the large number of collisions result in low throughput and

3 A shorter turnaround time can normally be achieved, resulting in betterperformance.

10 15 20 25 30 35 40 45 500

1

2

3

4

5

6

7

8

9

10

Number of Active Nodes (n)

Thr

ough

put (

Mbp

s)

k=6k=8k=10k=12Throughput of IEEE 802.11

Figure 12. Throughput comparison (simulation).

long delay (due to abundant retransmissions). This effect be-comes more evident for the network with more nodes (and thushigher contention). When k is reasonably large (e.g., k = 10or 12), the system with up to 50 active nodes can achieve thethroughput about 9.8 Mbps and the average delay lower than100 ms. As shown in figure 12, SYN-MAC achieves signifi-cantly higher throughput compared with IEEE 802.11 undersimilar traffic load. Additionally, SYN-MAC exhibits fairnessamong all active nodes, as we can see from figure 13, whereevery node has similar throughput with small variation aroundthe average.

We have also simulated a multi-hop wireless network witha grid topology that includes 25 × 25 = 625 nodes. The dis-tance between two adjacent nodes is 1 unit. The transmissionrange of a node is r . To eliminate the edge effect (i.e., nodesat the network edge tend to experience lower contention), we

0 5 10 15 20 25 30 35 400

50

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250

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Index of Active Nodes (n)

Num

ber

of n

ode

succ

esse

s

1hop−k=61hop−k=12

Figure 13. Fairness of SYN-MAC (simulation).

A DISTRIBUTED MEDIUM ACCESS CONTROL PROTOCOL FOR SYNCHRONIZED WIRELESS NETWORKS 635

6 7 8 9 10 11 120

50

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150

200

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Number of Contention slots(k)

Thr

ough

put (

Mbp

s)

r=1r=3r=5

Figure 14. Throughput in a grid network (simulation).

consider merely the core of the network, where all (16×16 =256) nodes in the core have the same number of neighbors.Figure 14 shows the total throughput of core with 16 × 16nodes. For r = 5 units, each node has about 80 neighbors,thus experiencing very high contention. The throughput riseswith an increase in k (though not obvious from the figure),because larger k helps resolve contention under heavy traf-fic load. Delay performance is illustrated in figure 15. Whenr = 1, each node has only four neighbors. Hence, the channelcontention is very low, leading to high throughput and lowdelay. With the increase of r , contention grows, and thus thedelay becomes longer. Due to the scale of figure 15 (in orderto show the results with different r values), the delay changewith respect to k becomes not apparent. In fact, the number ofcontention slots (k) has similar affects on the delay as demon-strated in figure 11. More specifically, when contention is low(i.e., r = 1), a small k results in low delay because of small

6 7 8 9 10 11 120

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Ave

rage

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ay (

ms)

r=5r=3r=1

Figure 15. Delay in a grid network (simulation).

10 15 20 25 30 35 4016.5

17

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Number of Active Nodes (n)

Thr

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s)

k=8k=6

Figure 16. Throughput in a random network (simulation).

overhead. On the other hand, if contention is high (i.e., r = 5),a large k is needed to resolve the contention problem.

In addition, we have simulated the networks with randomlydistributed nodes in an area of 500 × 500 m, and each nodehas a transmission range of 210 m. The throughput as a func-tion of n is depicted in figure 16. Note that, although there are10-40 active stations (similar to the case in figure 10), actualcontention in the multi-hop network is much lighter becausethe channel can be spatially reused and not all nodes are com-peting with each other. Thus, with an increase in the numberof stations (i.e., with network size growth), the total networkthroughput increases monotonically, until it reaches a certainn value (e.g., n = 30 for k = 6). Similar to what can be foundin figure 10, k = 10 in this figure results in best throughput.The delay in the network with a random topology is similar tothat in the grid network as discussed above, according to oursimulation outcomes. Thus, the results are omitted here.

SYN-MAC achieves significantly better performance com-pared with existing protocols according to the results (thoughnot shown here) reported in the literature. For example, themaximum channel efficiency of ADHOC MAC is only 75%[4], while SYN-MAC can readily exceed 90% channel effi-ciency with a properly chosen k value. The CSMA/CP pro-tocol [28] may yield zero collision probability, but its seriousunfairness is not acceptable in most distributed wireless net-works. Other protocols discussed in Section 2 are not compa-rable with SYN-MAC, because they are designed for wirelessnetworks either with centralized controller or without timesynchronization, thus inappropriate for synchronized multi-hop wireless networks; if employed, such a protocol performsmuch worse than SYN-MAC or may even fail altogether.

5. Conclusion

In this paper, we have proposed a novel medium access con-trol (MAC) protocol, called SYN-MAC, for synchronized

636 WU ET AL.

multi-hop wireless networks. SYN-MAC is a distributed, sim-ple, robust, efficient, fair, and QoS-capable MAC protocolthat effectively resolves channel contention and deals withthe hidden station problem in wireless networks. We haveevaluated SYN-MAC in terms of collision probability, packetdelay, and system throughput, via both analysis and simu-lation. Our results show that a network system using SYN-MAC can achieve a low collision probability, packet delaytolerance, and very high channel efficiency (exceeding 90%)under a wide range of traffic load. In our future work, we shallimplement the proposed SYN-MAC protocol in our wirelessnetwork testbed, and investigate into the overall system perfor-mance under different transport and network layer protocols.SYN-MAC could be standardized and serve as an alterna-tive to IEEE 802.11 for the mobile stations in synchronizednetworks.

Acknowledgment

We would like to thank Yijun Li at the Center for AdvancedComputer Studies, University of Louisiana at Lafayette forhis help on our simulation.

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Hongyi Wu is currently a tenure-track AssistantProfessor in the Center for Advanced ComputerStudies (CACS), University of Louisiana (UL) atLafayette. He received his Ph.D. degree in computerscience and M.S. degree in electrical engineeringfrom State University of New York (SUNY) at Buf-falo in 2002 and 2000, respectively. He received hisB.S. degree in scientific instruments from ZhejiangUniversity in 1996. His research interests includewireless mobile ad hoc networks, wireless sensor

networks, next generation cellular systems, and integrated heterogeneouswireless systems. He has served as symposium chair, session chair, and tech-nical committee member of several IEEE conferences, and a guest editorof ACM MONET special issue on Integration of Heterogeneous WirelessTechnologies. He has published more than two dozens of technical papers inleading journals and conference proceedings.E-mail: wu@cacs.louisiana.edu

Anant P. Utgikar (S’03) graduated with B.Tech. inElectrical Engineering from IIT—Bombay in 2001.He received M.S. in Computer Engineering fromUniv. of Louisiana at Lafayette (UL Lafayette) in2003. Presently he is working towards Ph.D. at ULLafayette. His research interests include computernetworking, logic design, software, simulation, mo-bile computing and distributed systems. His con-tributions to network simulator NS2 were rankedin top-5 of over 240,000 pages by Google. He has

won many programming competitions, IEEE, IEE technical paper presenta-tion contests as undergraduate and High School Science-Math Olympiads inIndia. He was honored by Govt. of India for outstanding performance at na-tional level in XII-th. He has authored a book chapter on Reservation Based

MAC protocols. He has published in IEEE ICNP’03 , IEEE SiPS’03 and IEEECAMP’03. He was invited with travel grant to NS2 workshop’02 at USC/ISI,ICNP’03 and SiPS’03. He has been in organizing team of IEEE CAMP 2003and CyberSecurity Workshop 2003. He has served as Reviewer for IEEE-VTCand ACM-MONET. He has held positions of Student Government Senatorand Secretary, Graduate Students Organization at UL Lafayette. He has con-tributed as volunteer to National Science-Technology-Math ESTME Weekorganised by NSF and DoE, USA.E-mail: utgikar@cacs.louisiana.edu

Nian-Feng Tzeng received the Ph.D. degree inComputer Science from the University of Illinois atUrbana-Champaign. Since 1987, he has been withCenter for Advanced Computer Studies, the Univer-sity of Louisiana at Lafayette, where he is currentlya professor. His current research interest is in theareas of computer communications and networks,high-performance computer systems, parallel anddistributed processing and fault-tolerant computing.He was on the editorial board of the IEEE Transac-

tions on Parallel and Distributed Systems, 1998–2001, and on the editorialboard of the IEEE Transactions on Computers, 1994–1998. He served as aDistinguished Visitor of the IEEE Computer Society, 1994–1997, and was theChair of Technical Committee on Distributed Processing, the IEEE ComputerSociety, from 1999 till 2002. He has been on the technical program commit-tees of various conferences and will serve as the Technical Program Chair ofthe 10th International Conference on Parallel and Distributed Systems, July2004.

Dr. Tzeng is the recipient of the outstanding paper award of the 10th In-ternational Conference on Distributed Computing Systems, May 1990. Hereceived the University Foundation Distinguished Professor Award in 1997.E-mail: tzeng@cacs.louisiana.edu