Joint Routing and Scheduling in Wireless Mesh Networks based on Traffic Prediction Using ARIMA

Abstract

Wireless Mesh Networks offer a high-performance and low-cost solution to last-mile broadband Internet access. Routing and Scheduling play a critical role in determining the performance of a wireless mesh network. Efficiency of Routing and Scheduling algorithms is highly dependent on the availability of accurate traffic information. In this paper, we predict network traffic based on past data using ARIMA model, and provide that input to the routing and scheduling algorithm. Joint routing and scheduling results in significant performance improvement over the routing only algorithms. So, we provide predicted network traffic information to a Joint routing and scheduling algorithm known as Traffic Oblivious Routing and Scheduling. Traffic Oblivious Routing and Scheduling algorithm optimizes the worst case performance under traffic uncertainty but when accurate traffic information is available to the algorithm, its performance is enhanced. In the Traffic Oblivious Routing and Scheduling algorithm, computing the routing and the scheduling values is a one time overhead. In this paper, we present a system where we predict network traffic information using past data, then use the predicted information to formulate the input for the Traffic Oblivious routing and scheduling algorithm and finally we evaluate the performance of the algorithm using simulations.