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Enhance & Explore: an Adaptive Algorithm to Maximize the Utility of Wireless Networks
"... 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 timevarying and not known explicitly. Hence, as the capacity region is imposs ..."
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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 timevarying and not known explicitly. Hence, as the capacity region is impossible to know or measure exactly, existing scheduling schemes either underestimate it and are too conservative, or they overestimate 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 congestioncontrol, the E&E algorithm greatly increases the utility achieved by multihop networks as well.