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A Measurement-Based Algorithm to Maximize the Utility of Wireless Networks
Citation key HAMST-AMAMUWN-11
Author Herzen, Julien and Aziz, Adel and Merz, Ruben and Shneer, Seva and Thiran, Patrick
Title of Book Proceedings of the 3rd ACM workshop on Wireless of the students, by the students, for the students (S3 '11)
Pages 13–16
Year 2011
ISBN 978-1-4503-0868-7
DOI http://dx.doi.org/10.1145/2030686.2030691
Location Las Vegas, NV, USA
Address New York, NY, USA
Month September
Publisher ACM
Abstract The goal of jointly providing fairness and efficiency in wireless networks can be seen as the problem of maximizing a given utility function. The main difficulty when solving this problem is that the capacity region of wireless networks is typically unknown and time-varying, which prevents the usage of traditional optimization tools. As a result, scheduling and congestion control algorithms are either too conservative because they under-estimate the capacity region, or suffer from congestion collapse because they over-estimate it. We propose a new adaptive congestion control algorithm, called Enhance & Explore (E\&E). It maximizes the utility of the network without requiring any explicit characterization of the capacity region. E\&E works above the MAC layer and is decoupled from the underlying scheduling mechanism. It provably converges to a state of optimal utility. We evaluate the performance of the algorithm in a WLAN setting, using both simulations and measurements on a real testbed composed of IEEE 802.11 wireless routers.
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