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Rate Adaptation in Congested Wireless Networks through Real-Time Measurements
November 2010 (vol. 9 no. 11)
pp. 1535-1550
Prashanth A.K. Acharya, University of California Santa Barbara, Santa Barbara
Ashish Sharma, University of California Santa Barbara, Santa Barbara
Elizabeth M. Belding, University of California Santa Barbara, Santa Barbara
Kevin C. Almeroth, University of California Santa Barbara, Santa Barbara
Konstantina (Dina) Papagiannaki, Intel Research, Pittsburgh
Rate adaptation is a critical component that impacts the performance of IEEE 802.11 wireless networks. In congested networks, traditional rate adaptation algorithms have been shown to choose lower data-rates for packet transmissions, leading to reduced total network throughput and capacity. A primary reason for this behavior is the lack of real-time congestion measurement techniques that can assist in the identification of congestion-related packet losses in a wireless network. In this work, we first propose two real-time congestion measurement techniques, namely an active probe-based method called Channel Access Delay, and a passive method called Channel Busy Time. We evaluate the two techniques in a testbed network and a large WLAN connected to the Internet. We then present the design and evaluation of Wireless cOngestion Optimized Fallback (WOOF), a rate adaptation scheme that uses congestion measurement to identify congestion-related packet losses. Through simulation and testbed implementation we show that, compared to other well-known rate adaptation algorithms, WOOF achieves up to 300 percent throughput improvement in congested networks.

[1] J. Horrigan, Memo on Wireless Internet Access, Pew Internet and American Life Project, http://www.pewinternet.org/pdfsPIP_ Wireless.Use.pdf , Feb. 2007.
[2] A.P. Jardosh, K. Mittal, K.N. Ramachandran, E.M. Belding, and K.C. Almeroth, "IQU: Practical Queue-Based User Association Management for WLANs," Proc. ACM MobiCom, Sept. 2006.
[3] M. Rodrig, C. Reis, R. Mahajan, D. Wetherall, and J. Zahorjan, "Measurement-Based Characterization of 802.11 in a Hotspot Setting," Proc. ACM SIGCOMM Workshop Experimental Approaches to Wireless Network Design and Analysis (EWIND), Aug. 2005.
[4] A. Jardosh, K. Ramachandran, K. Almeroth, and E. Belding-Royer, "Understanding Congestion in IEEE 802.11b Wireless Networks," Proc. Internet Measurement Conf., Oct. 2005.
[5] P. Acharya, A. Sharma, E. Belding, K. Almeroth, and K. Papagiannaki, "Congestion-Aware Rate Adaptation in Wireless Networks: A Measurement-Driven Approach," Proc. Fifth Ann. IEEE Conf. Sensor, Mesh and Ad Hoc Comm. and Networks (SECON), June 2008.
[6] J. Kim, S. Kim, S. Choi, and D. Qiao, "CARA: Collision-Aware Rate Adaptation for IEEE 802.11 WLANs," Proc. IEEE INFOCOM, Apr. 2006.
[7] X. Yang and N. Vaidya, "On the Physical Carrier Sense in Wireless Ad Hoc Networks," Proc. IEEE INFOCOM, Mar. 2005.
[8] G. Holland, N. Vaidya, and P. Bahl, "A Rate-Adaptive MAC Protocol for Multi-Hop Wireless Networks," Proc. ACM MobiCom, July 2001.
[9] G. Judd, X. Wang, and P. Steenkiste, "Efficient Channel-Aware Rate Adaptation in Dynamic Environments," Proc. ACM MobiSys, June 2008.
[10] A. Kamerman and L. Monteban, "WaveLAN II: A High-Performance Wireless LAN for the Unlicensed Band," Bell Labs Technical J., vol. 2, no. 3, pp. 118-133, Aug. 1997.
[11] M. Lacage, M. Manshaei, and T. Turletti, "IEEE 802.11 Rate Adaptation: A Practical Approach," Proc. Seventh ACM Int'l Symp. Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM), Oct. 2004.
[12] J. Bicket, "Bit-Rate Selection in Wireless Networks," master's thesis, Massachusetts Inst. of Tech nology, 2005.
[13] S.H.Y. Wong, S. Lu, H. Yang, and V. Bharghavan, "Robust Rate Adaptation for 802.11 Wireless Networks," Proc. ACM MobiCom, Sept. 2006.
[14] M. Heusse, F. Rousseau, R. Guillier, and A. Duda, "Idle Sense: An Optimal Access Method for High Throughput and Fairness in Rate Diverse Wireless LANs," Proc. ACM SIGCOMM, Aug. 2005.
[15] M. Heusse, F. Rousseau, G. Berger-Sabbatel, and A. Duda, "Performance Anomaly of 802.11b," Proc. IEEE INFOCOM, Apr. 2003.
[16] Y. Hu and D. Johnson, "Exploiting Congestion Information in Network and Higher Layer Protocols in Multihop Wireless Ad Hoc Networks," Proc. Int'l Conf. Distributed Computing Systems, Mar. 2004.
[17] Q. Xue and A. Ganz, "Ad Hoc QoS On-Demand Routing (AQOR) in Mobile Ad Hoc Networks," J. Parallel and Distributed Computing, vol. 63, no. 2, pp. 154-165, 2003.
[18] A. Sharma, M. Tiwari, and H. Zheng, "MadMAC: Building a Reconfigurable Radio Testbed Using Commodity 802.11 Hardware," Proc. First IEEE Workshop Networking Technologies for Software Defined Radio Networks, Sept. 2006.
[19] W. Baumgartner, P. Weiß, and H. Schindler, "A Nonparametric Test for the General Two-Sample Problem," Biometrics, vol. 54, no. 3, pp. 1129-1135, 1998.
[20] C. Reis, R. Mahajan, M. Rodrig, D. Wetherall, and J. Zahorjan, "Measurement-Based Models of Delivery and Interference in Static Wireless Networks," Proc. ACM SIGCOMM, Sept. 2006.
[21] Linux Wireless, http:/www.linuxwireless.org, June 2009.
[22] Netdisco—Network Discovery and Management, http:/www.netdisco.org, June 2009.
[23] IEEE Std. 802.11k-2008, Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications Amendment 1: Radio Resource Management of Wireless LANs, IEEE, June 2008.
[24] A. Jardosh, K. Ramachandran, K. Almeroth, and E. Belding-Royer, "Understanding Link-Layer Behavior in Highly Congested IEEE 802.11b Wireless Networks," Proc. ACM SIGCOMM Workshop Experimental Approaches to Wireless Network Design and Analysis (EWIND), Aug. 2005.
[25] D.S.J. De Couto, D. Aguayo, J. Bicket, and R. Morris, "A High-Throughput Path Metric for Multi-Hop Wireless Routing," Proc. ACM MobiCom, Oct. 2003.
[26] K. Ramachandran, H. Kremo, M. Gruteser, P. Spasojevic, and I. Seskar, "Experimental Scalability Analysis of Rate Adaptation Techniques in Congested 802.11 Networks," Proc. IEEE Int'l Symp. World of Wireless, Mobile and Multimedia Networks (WoWMoM), June 2007.
[27] H. Lundgren, K. Ramachandran, E. Belding-Royer, K. Almeroth, M. Benny, A. Hewatt, A. Touma, and A. Jardosh, "Experiences from the Design, Deployment, and Usage of the UCSB MeshNet Testbed," IEEE Wireless Comm., vol. 13, no. 2, pp. 18-29, Apr. 2006.
[28] J. Bicket, D. Aguayo, S. Biswas, and R. Morris, "Architecture and Evaluation of an Unplanned 802.11b Mesh Network," Proc. ACM MobiCom, Aug. 2005.
[29] Qualnet Network Simulator, Version 4.0, http:/www. scalable-networks.com, 2008.

Index Terms:
Wireless communication, access schemes, algorithm/protocol design and analysis.
Citation:
Prashanth A.K. Acharya, Ashish Sharma, Elizabeth M. Belding, Kevin C. Almeroth, Konstantina (Dina) Papagiannaki, "Rate Adaptation in Congested Wireless Networks through Real-Time Measurements," IEEE Transactions on Mobile Computing, vol. 9, no. 11, pp. 1535-1550, Nov. 2010, doi:10.1109/TMC.2010.108
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