ACM Transactions on Computer Systems (TOCS)
Aziala-net: deploying a scalable multi-hop wireless testbed platform for research purposes
Proceedings of the 2009 MobiHoc S3 workshop on MobiHoc S3
Enhance & explore: an adaptive algorithm to maximize the utility of wireless networks
MobiCom '11 Proceedings of the 17th annual international conference on Mobile computing and networking
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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.