Starvation modeling and identification in dense 802.11 wireless community networks

With the,rowing number of spontaneously deployed WiFi hotspots and home networks, end-users often experience significant performance degradation or even starvation. However, we observe that tuning individual system parameters (channel, Tx power, carrier sense (CS) threshold, and transmit rate etc.) is insufficient and in some cases may lead to starvation. In this paper, we develop a comprehensive analytical model to characterize throughput of individual flows in dense IEEE 802.11 wireless community networks. The proposed model subsumes existing models for the IEEE 802.11 MAC in multihop wireless networks by accounting for heterogeneous transmission power levels and CS thresholds, as well as various sources of packet collisions. Based on the insight from the theoretical analysis and simulation results, we propose a simple identification mechanism that determines the sources of starvation using local measurements. Both the theoretical model and the identification algorithm are validated using ns-2 simulations.