A smart exponential-threshold-linear backoff mechanism for IEEE WLANs

Transcription

1 INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS Int. J. Commun. Syst. 2011; 24: Published online 13 January 2011 in Wiley Online Library (wileyonlinelibrary.com) A smart exponential-threshold-linear backoff mechanism for IEEE WLANs Chih-Heng Ke 1, Chih-Cheng Wei 2, Kawuu W. Lin 2,, and Jen-Wen Ding 3 1 Department of Computer Science and Information Engineering, National Quemoy University, Kinmen, Taiwan 2 Department of Computer Science and Information Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan 3 Department of Information Management, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan SUMMARY Based on the standardized IEEE Distributed Coordination Function (DCF) protocol, this paper proposes a new backoff mechanism, called Smart Exponential-Threshold-Linear (SETL) Backoff Mechanism, to enhance the system performance of contention-based wireless networks. In the IEEE DCF scheme, the smaller contention window (CW) will increase the collision probability, but the larger CW will delay the transmission. Hence, in the proposed SETL scheme, a threshold is set to determine the behavior of CW after each transmission. When the CW is smaller than the threshold, the CW of a competing station is exponentially adjusted to lower collision probability. Conversely, if the CW is larger than the threshold, the CW size is tuned linearly to prevent large transmission delay. Through extensive simulations, the results show that the proposed SETL scheme provides a better system throughput and lower collision rate in both light and heavy network loads than the related backoff algorithm schemes, including Binary Exponential Backoff (BEB), Exponential Increase Exponential Decrease (EIED) and Linear Increase Linear Decrease (LILD). Copyright 2011 John Wiley & Sons, Ltd. Received 20 April 2010; Revised 9 August 2010; Accepted 11 October 2010 KEY WORDS: DCF; backoff algorithm; contention window; BEB; EIED; LILD 1. INTRODUCTION Wireless local area networks (WLANs) have recently gained widespread popularity and have consequently become ubiquitous in our society. An increasing number of wireless mobile computing devices are being introduced, including portables, palmtops and personal digital assistants. WLANs have been successfully adopted in many domains, such as health-care, manufacturing, retail outlets, warehousing, libraries and academia. WLANs have been widely deployed and thus people can now easily access the Internet using wireless services, and nowadays are quite familiar with transmitting multimedia contents, voice and video over WLANs. The dominant standard for WLANs is the IEEE protocol [1]; It includes detailed specifications both for Medium Access Control (MAC) and Physical Layer (PHY). In WLANs, the media constituting PHY is shared by all mobile stations and has a limited connection range. The MAC protocol provides the contention-free Point Coordination Function (PCF) and the contention-based Distributed Coordination Function (DCF) to access the shared wireless channel. The results of many studies have shown that currently designed PCF is not able to guarantee sufficient QoS Correspondence to: Kawuu W. Lin, Department of Computer Science and Information Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan. linwc@cc.kuas.edu.tw Copyright 2011 John Wiley & Sons, Ltd.

2 1034 C.-H. KE ET AL. [2 4]. Further, the DCF is imperative for IEEE products. Therefore, we will only focus on how to improve the performance of IEEE DCF. In the IEEE protocol, DCF is the fundamental method of access used to support asynchronous data transfer on a best effort basis. The DCF is based on Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA), in which all stations compete for the wireless channel with the same priority. Binary Exponential Backoff (BEB) with CSMA/CA is employed as a scheme of obtaining stability and enabling the media to be shared. At the first transmission attempt of a packet, all competing stations randomly select the backoff time according to the BEB scheme which is set from a uniform distribution over the interval [0,CW min 1], where CW min is the minimum contention window (CW) size. Every time a station experiences transmission collision, the CW size doubles up to its maximum CW max. And the new CW is used for the following transmission attempt. Following a successful transmission, the station resets its CW size to the minimum size. However, the CW resetting mechanism of BEB causes a very large variation in the CW size, and degrades the performance of a network when it is heavily loaded since each new packet starts with the CW min, which increases the probability of collision. Accordingly, there have been many proposals for improving the performance. The mechanism of Exponential Increase Exponential Decrease (EIED) [5] suggests a slower reduction of the CW after a successful transmission. In the EIED mechanism, the CW is doubled after a collision and halved after a successful transmission. This improves the performance if the number of competing stations is large. The CW size is thus kept large in order to avoid frequent collisions, but the rapid variations in CW size may be too sensitive to adapt to the network load. Another algorithm, Linear Increase Linear Decrease (LILD), which is based on Multiple Increase Linear Decrease (MILD) originally proposed in [6], provides better performance than DCF and EIED mechanisms when the number of stations is large. In the LILD mechanism, the CW is plus one or CW min after a collision and minus one or CW min after a successful transmission. Other contention resolution mechanisms have also been proposed to improve the network performance of IEEE DCF. Most of them, however, require an exchange of information between stations and complicated computation [7 10]. These algorithms are not considered here and we consider only acknowledgment based on the backoff algorithm. The remainder of this paper is organized as follows. Section 2 reviews the DCF and describes various schemes presented in the literature that were designed to improve the performance of contention-based wireless networks. Section 3 introduces the proposed scheme and presents an analytical model in detail. Model validation, a simulation and experimental results are presented in Section 4. Section 5 concludes the paper and discusses future works. 2. RELATED WORKS 2.1. IEEE DCF DCF is the primary access protocol of the IEEE standard for stations to share the wireless medium with the same priority. DCF is basically a CSMA/CA. Each station with a new packet ready for transmission monitors the channel activity. If a station senses that the medium has been idle, the transmission may begin. If it senses that the channel is busy, the station will wait until it senses that the medium is idle again after which the station is then allowed to transmit. The basic access mechanism of DCF is shown in a simple diagram in Figure 1. First, a station with a new packet to transmit senses the channel state until it senses that the channel is idle, then waits longer for a DIFS period and generates a backoff time in a CW state. The IEEE DFC uses the BEB algorithm. The backoff timer is uniformly chosen in the range (0, W i 1). CW is also known as contention window, which is an integer with the range determined by the PHY characteristics between a minimum value of CW min and a maximum value of CW max,andwithw i as the current CW. The number of failed transmissions of the same packet is represented by i. At the first transmission attempt, the CW is set at W 0 =CW min. After each unsuccessful transmission, CW is doubled and W i =2 W i 1 =2 i CW min, until the maximum value CW max =2 m CW min is

3 AN SETL BACKOFF MECHANISM FOR IEEE WLANS 1035 Figure 1. Basic mechanism of DCF. Figure 2. Backoff algorithm for the DCF scheme. Figure 3. CW variation in the BEB scheme. reached. m is the maximum number of backoff stages. Conversely, for each successful transmission, CW will reset to the minimum value CW min. In the IEEE DCF standard for the Direct Sequence Spread Spectrum (DSSS) physical channel, CW min =32, CW max =1024 and m =5. Figure 2 presents a diagram of the transitions in a backoff stage in the BEB scheme. The values CW min and CW max are assumed to be 32 and The CW variations of the BEB scheme are illustrated in Figure 3.

4 1036 C.-H. KE ET AL. Figure 4. Backoff algorithm for the EIED scheme. Figure 5. CW variation in the EIED scheme EIED backoff scheme As mentioned in Section 2.1, the IEEE DCF uses the BEB scheme to enable active stations to compete accessing the medium. Another alternative backoff scheme, called EIED [5], has been proposed in order to lower the collision probability and improve performance. In EIED, whenever a packet transmitted from a station is involved in a collision, the CW size for that station is increased by backoff factor r I, and the CW for that station is decreased by backoff factor r D after a successful transmission. The EIED backoff algorithm is represented by the following: W i =min[ri W i 1,CW max ] for a collision, and W i =max[w i 1 /r D,CW min ] for a successful transmission. For r I =r D =2, the CW both increases and decreases exponentially. Whenever a successful transmission occurs, this does not mean that the number of competing stations has been reduced. Thus, to prevent CW from immediately returning to the initial state CW min and increasing the probability of collision, the EIED aims to reduce the CW slowly, exponentially, after a successful transmission. A diagram of the transitions in a backoff stage for EIED is shown in Figure 4, and variations in the CW in the EIED scheme are shown in Figure LILD scheme In [5], another backoff scheme is proposed, called MILD; after a successful transmission the CW is reduced by one to CW min, and multiplied by 1.5 to the maximum CW max. The backoff algorithm

5 AN SETL BACKOFF MECHANISM FOR IEEE WLANS 1037 Figure 6. Backoff algorithm for the LILD scheme. of MILD could be expressed as follows: W i =min[wi 1 1.5,CW max] for a collision, and W i =max[w i 1 1,CW min ] for a successful transmission. The LILD scheme also represents an improvement of the MILD mechanism, as it increases and decreases the CW size linearly. Therefore, regardless of whether a transmission succeeds or fails, the CW changes with the value of CW min, and is also limited by CW max and CW min. The backoff algorithm of LILD is represented by the following. W i =min[w i 1 +CW min,cw max ] for a collision, and W i =max[w i 1 CW min,cw min ] for a successful transmission. The LILD linearly slows down or increases the variations in CW. When a station faces many collision incidents and its CW is in the higher region, a slow linear decrease in CW after successful transmission will help resolve contention. The network load may be still heavy. Keeping the CW in the higher region can help avoid contention occurrence. A diagram of the transitions in a backoff stage for LILD is shown in Figure Comparison of the related works For contention-based DCF, the adjustment of CW is very important. A proper tuning of the CW resolution mechanism that is coordinated with the network load will improve the system s throughput and prevent transmission collision. As mentioned above, the EIED mechanism provides a rapid variation of CW, and is suitable for an environment with fewer competing stations and a light network load. The LILD, on the other hand, changes the CW slowly, which makes it suitable for heavy network loads with a large number of competing stations. There is a tradeoff between the waste of transmission time and the risk of collision followed by retransmission. To address this tradeoff, we propose a new backoff algorithm, called Smart Exponential Threshold Linear backoff algorithm scheme (SETL), that combines the advantages of EIED and LILD. Furthermore, we adjust the policy after a successful transmission to further improve the performance of IEEE DCF. 3. THE PROPOSED SCHEME As shown in the comparison in Section 2, the EIED mechanism performs better than the LILD mechanism with a light network load of less competing stations. Conversely, the LILD mechanism performs better than the EIED mechanism when the network load is heavy with more competing stations. In order to enhance the performance in both a light and heavy network load environment, we combine the advantages of the EIED and LILD mechanisms in order to adapt to the conditions of a wireless network. In the proposed SETL backoff algorithm, a threshold value of CW, CW Threshold, is set in order to determine whether there are more or less competing stations in the WLANs. If the current CW size of a competing station is more than the CW Threshold, the CW is in the higher region, which means that the competing station has retransmitted many times due to a collision

6 1046 C.-H. KE ET AL Normalized saturation throughput with different counter 'S' Normalized Saturation Throughput "stations=10" "stations=30" "stations=50" "stations=70" "stations=90" "stations=110" "stations=130" "stations=150" Continuous consecutive successful counter 'S' Figure 15. Normalized saturation throughput with different counter S. Collision Rate (%) Collision rate with different counter 'S' "stations=10" "stations=30" "stations=50" "stations=70" "stations=90" "stations=110" "stations=130" "stations=150" Continuous consecutive successful counter 'S' Figure 16. Collision rate with different counter S. consecutive successful transmission counter S, the SETL scheme is stably tuned to prevent the CW from being directly reduced after each successful transmission, which invites the probability of collision. We validated our analysis model by means of simulations, and from the results of our experiments, we confirmed that the SETL works better than other related backoff schemes, offering higher saturation throughput and a lower collision rate. In our future work, we are interested in applying the SETL scheme to a contention-based wireless network of multi-rate environment. By adjusting the continuous consecutive successful transmission counter S to assign different transmitting priorities for different transmission rates, performance can be improved even further. REFERENCES 1. IEEE standard for Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications. ISO/IEC :1999(E), August Kuo WK, Chan CY, Chen KC. Time bounded services and mobility management in IEEE wireless LANs. Proceedings of the IEEE Personal Wireless Communication Conference, Mumbai, India, 1997;

7 AN SETL BACKOFF MECHANISM FOR IEEE WLANS Visser MA, Zarki ME. Voice and data transmission over an wireless network. Proceedings of the Personal, Indoor and Mobile Radio Communications Conference, Toronto, Ont., Canada, vol. 2, September 1995; Sanchez J, Martinez R, Marcellin MW. A survey of MAC protocols for wireless ATM. IEEE Network 1997; 11: Song N, Kwak B, Song J, Miller LE. Enhancement of IEEE distributed coordination function with exponential increase exponential decrease backoff algorithm. The 57th IEEE Semiannual Spring VTC, Orlando, FL, U.S.A., vol. 4, Bharghavan V, Demers A, Shenker S, Zhang L. MACAW: a media access protocol for wireless LAN s. Proceeding ACK SIGCOMM 94, London, England, Bianchi G, Fratta L, Oliveri M. Performance evaluation and enhancement of the CSMA/CA MAC protocol for wireless LANs. Proceedings of PIMRC 96, Taipei, Taiwan, October 1996; Cali F, Conti M, Gergori E. Dynamic tuning of the IEEE protocol to achieve a theoretical throughput limit. IEEE/ACM Transactions on Networking 2000; 8(6): Qiao D, Shin KG. UMAV: a simple enhancement to the IEEE DCF. Proceedings of the 36th Hawaii International Conference on System Science (HICSS-36), Hawaii, January Deng DJ, Ke CH, Chen HH, Huang YM. Contention window optimization for IEEE DCF access control. IEEE Transactions on Wireless Communications 2008; 7(12): Natkanies M, Pach AR. An analysis of the backoff mechanism used in IEEE networks. IEEE Symposium on Computer and Communication, Antibes-Juan les Pins, France, July 2000; Wu H, Peng Y, Long K, Cheng S. A simple model of IEEE Wireless LAN. IEEE International Conference on Info-tech and Info-net, Beijing, China, vol. 2, November 2001; Wu H, Cheng S, Peng Y, Long K, Ma J. IEEE distributed coordination function (DCF) analysis and enhancement. IEEE International Conference on Communications, New York, NY, U.S.A., vol. 1(28), May 2002; Kwak BJ, Song NO, Miller LE. Analysis of the stability and performance of exponential backoff. IEEE Wireless Communications and Networking Conference, New Orleans, LA, U.S.A., vol. 3(3), 2003; Xiao Y. Backoff-based priority schemes for IEEE IEEE International Conference on Communications 2003, Anchorage, AK, U.S.A., vol. 3, May 2003; Velkov ZH, Spasenovski B. Saturation throughput-delay analysis of IEEE DCF in fading channel. IEEE International Conference on Communications 2003, Anchorage, AK, U.S.A., vol. 1, May 2003; Chatzimisios P, Boucouvalas AC, Vitsas V. IEEE packet delay a finite retry limit analysis. IEEE Global Telecommunications Conference 2003, San Francisco, U.S.A., vol. 2, 2003; Chen H, Li Y. Performance model of IEEE DCF with variable packet length. IEEE Communications Letters 2004; 8(3): Bianchi G. Performance analysis of the IEEE distributed coordination function. IEEE Journal on Selected Areas in Communication 2000; 18(3): The Network Simulator NS-2. Available from: AUTHORS BIOGRAPHIES Chih-Heng Ke received his BS and PhD degrees in Electrical Engineering from the National Cheng-Kung University, in 1999 and He is an assistant professor of Computer Science and Information Engineering, in the National Quemoy University, Kinmen, Taiwan. His current research interests include multimedia communications, wireless network, and QoS network. Chih-Cheng Wei received the BS degree from the Electrical Engineering Department, National Central University, Taiwan in 1991 and the MS degree in Computer Science and Information Engineering from the National Kinmen Institute of Technology, Kinmen, Taiwan in He is now a PhD student in the Electronics Department of the National Kaohsiung University of Applied Sciences. His research interests are performance evaluation and optimization in wireless networks.

8 1048 C.-H. KE ET AL. Kawuu W. Lin received the BS from the Department of Computer Science and Information Engineering, National Taiwan University (NTU), Taiwan, 1999, and received his PhD from the Department of Computer Science and Information Engineering, National Cheng-Kung University (NCKU), Taiwan, Since August 2007, he has been an assistant professor in the Department of Computer Science and Information Engineering, National Kaohsiung University of Applied Sciences (KUAS), Taiwan. His research interests include data mining and its applications, sensor technologies, and parallel and distributed computing. He is a member of Phi Tau Phi honorary society, and has won the Phi Tau Phi Scholastic Honor in Jen-Wen Ding is an Associate Professor in the Department of Information Management, the National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan. He received his BS, MS, and PhD degrees in Engineering Science from the National Cheng Kung University, Tainan, Taiwan, in 1996, 1998, and 2001, respectively. His research interests include video streaming and multimedia communications. He has authored/co-authored over 30 refereed papers in journals, conference, and workshop proceedings. He also holds several patents in multimedia storage and communications. He received the Best Paper Award of 2007 Asia-Pacific Workshop on Visual Information Processing (VIP 2007) and Acer Long-Term Prize in Dr Ding was the Editor of the proceeding of 2008 Pacific-Rim Conference on Multimedia (PCM 2008) and the Guest Editor of the Special Issue on Ubiquitous Multimedia Computing: Systems, Networking, and Applications for International Journal of Ad Hoc and Ubiquitous Computing (IJAHUC). He has been invited to serve on the technical program committee at many national and international conferences. He is also a member of the IEEE as well as of IEEE Circuits and Systems Society.