Channel switching control policy for wireless mesh networks
Dynamic channel assignment algorithms allow wireless nodes to switch channels when their traffic loads exceed certain thresholds. These thresholds represent estimations of their throughput capacities. Unfortunately, the threshold estimation may not be accurate due to co-channel interference (CCI) and adjacent-channel interference (ACI), especially with high traffic loads in dense networks. When the link capacity is over-estimated, these channel assignment algorithms are not effective. This is because the channel switch is not triggered even with overloaded data traffic and the link quality decreases significantly as the channel is overloaded. When the link capacity is under-estimated, the link is under-utilized. Moreover, when link traffic load increases from time to time, channel switch occurs frequently. Such frequent channel switches increase latency and degrade throughput, and can even cause network wide channel oscillations. In this paper, we propose a novel threshold-based control system, called balanced control system (BCS). The proposed threshold-based control policy consists of deciding, according to the real time traffic load and interference, whether to switch to another channel, which channel should be switched to and how to perform the switch. Our control model is based on a fuzzy logic control. The threshold which assists to make the channel switch decisions, could be deduced dynamically according to the real-time traffic of each node. We also design a novel dynamic channel assignment scheme, which is used for the selection of the new channel. The channel switch scheduler is provided to perform channel-switch processing for sender and receiver over enhanced routing protocols. We implement our system in NS2, and the simulation results show that with our proposed system, the performance improves by 12.3%72.8% in throughput and reduces 23.2%52.3% in latency.
wireless mesh network dynamic channel assignment balanced control system real-time adaptive