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Issue No.11 - November (2010 vol.9)
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.
Wireless communication, access schemes, algorithm/protocol design and analysis.
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, November 2010, doi:10.1109/TMC.2010.108
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