Integrating traffic estimation and dynamic channel reconfiguration in Wireless Mesh Networks

Careful Channel Assignment (CA) and Link Scheduling (LS), tuned to the traffic demand in the network, are required to efficiently utilize Multi-Channel Multi-Radio (MC-MR) Wireless Mesh Networks (WMNs). In a dynamic network, where the traffic demand keeps changing with time, we need to reconfigure the CA and LS to suit to the changing demands. But, a change in CA leads to disruption of traffic resulting in a less reliable and lossy network. In this paper, we propose a theoretical framework to evaluate the efficiency of channel reconfiguration by taking into consideration the two conflicting objectives of maximizing network throughput and minimizing the reconfiguration overhead. A channel reconfiguration scheme that takes into account the current state of the network can find a new CA with significantly less overhead caused by reconfiguration. We propose and evaluate polynomially bounded heuristic algorithms for performing demand-based and state aware channel reconfiguration. Further, in a highly dynamic network scenario, performing reconfiguration very frequently to suit every traffic demand will lead to high reconfiguration overhead. Whereas doing it less frequently will lead to underutilization of the network. Hence, we propose a scheme that employs prediction techniques to estimate the future traffic demands in order to reduce the frequency of reconfiguration considering the long term traffic demand and conduct simulation studies to evaluate this scheme.