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Enhance & Explore: an Adaptive Algorithm to Maximize the Utility of Wireless Networks
Citation key AHMST-EEAAMUWN-11
Author Aziz, Adel and Herzen, Julien and Merz, Ruben and Shneer, Seva and Thiran, Patrick
Title of Book 17th International Conference on Mobile Computing and Networking (Mobicom '11)
Pages 157–168
Year 2011
ISBN 978-1-4503-0492-4
DOI http://dx.doi.org/10.1145/2030613.2030632
Location Las Vegas, NV, USA
Address New York, NY, USA
Month September
Publisher ACM
Organization ACM SIGMOBILE
Abstract The goal of jointly providing efficiency and fairness in wireless networks can be seen as the problem of maximizing a given utility function. In contrast with wired networks, the capacity of wireless networks is typically time-varying and not known explicitly. Hence, as the capacity region is impossible to know or measure exactly, existing scheduling schemes either under-estimate it and are too conservative, or they over-estimate it and suffer from congestion collapse. We propose a new adaptive 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 it does not demand any modification to the existing networking stack. We first evaluate our algorithm theoretically and we prove that it converges to a state of optimal utility. We then evaluate the performance of the algorithm in a WLAN setting, using both simulations and real measurements on a testbed composed of IEEE 802.11 wireless routers. Finally, we investigate a wireless mesh network setting and we find that, when coupled with an efficient mechanism for congestion-control, the E\&E algorithm greatly increases the utility achieved by multi-hop networks as well.
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