Congestion-Aware Rate Adaptation in Wireless Networks: A Measurement-Driven Approach

Prashanth Aravinda Kumar Acharya, Ashish Sharma, Elizabeth M. Belding, Kevin C. Almeroth, Konstantina Papagiannaki
<span title="">2008</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q4aeonhyuffk7bofdphs636qtq" style="color: black;">2008 5th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks</a> </i> &nbsp;
Traditional rate adaptation solutions for IEEE 802.11 wireless networks perform poorly in congested networks. Measurement studies show that congestion in a wireless network leads to the use of lower transmission data rates and thus reduces overall network throughput and capacity. The lack of techniques to reliably identify and characterize congestion in wireless networks has prevented development of rate adaptation solutions that incorporate congestion information in their decision framework.
more &raquo; ... this end, our main contributions in this paper are two-fold. First, we present a technique that identifies and measures congestion in an 802.11 network in real time. Second, we design Wireless cOngestion Optimized Fallback (WOOF), a measurement-driven rate adaptation scheme for 802.11 devices that uses the congestion measurement to identify congestion related packet losses. Through experimental evaluation, we show that WOOF achieves up to 300% higher throughput in congested networks, compared to other well-known adaptation algorithms. 978-1-4244-1777-3/08/$25.00 © IEEE This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE SECON 2008 proceedings.
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