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Summary: 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
Department of Computer Science, University of California, Santa Barbara CA 93106
Intel Research, Pittsburgh PA 15213
{acharya, asharma, ebelding, almeroth}@cs.ucsb.edu, dina.papagiannaki@intel.com
Abstract--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. To
this end, our main contributions in this paper are two-fold.
First, we present a technique that identifies and measures
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