Association Optimization in Wi-Fi Networks based on the Channel Busy Time Estimation.

With the centralized management paradigm offered by the recent IEEE 802.11 products, it is now easier and more efficient to optimize associations between access points (APs) and stations. Most of the optimization approaches consider a saturated network. Even if such traffic conditions are rare, the optimization of the association step under this assumption has the benefit to fairly share the bandwidth between stations. Nevertheless, traffic demands may be very different from one station to another and it may be more useful to optimize associations according to the stations’ demands. In this paper, we propose an optimization of the association step based on the stations’ throughputs and the channel busy time fraction (BTF). The latter is defined as the proportion of time the channel is sensed busy by an AP. Associations are optimized in order to minimize the greatest BTF in the network. This original approach allows the Wi-Fi manager/controller to unload the most congested AP, increase the throughput for most of the stations, and offer more bandwidth to stations that need it. We present a local search technique that finds local optima to this optimization problem. This heuristic relies on an analytical model that predicts BTF for any configuration. The model is based on a Markov network and a Wi-Fi conflict graph. NS-3 simulations including a large set of scenarios highlight the benefits of our approach and its ability to improve the performance in congested and non-congested Wi-Fi networks.