Video On-Demand Streaming in Cognitive Wireless Mesh Networks

Cognitive radio (CR), which enables dynamic access of underutilized licensed spectrums, is a promising technology for more efficient spectrum utilization. Since cognitive radio enables the access of larger amount of spectrum, it can be used to build wireless mesh networks with higher network capacity, and thus provide better quality of services for high bit-rate applications. In this paper, we study the multisource video on-demand application in multi-interface cognitive wireless mesh networks. Given a video request, we find a joint multipath routing and spectrum allocation for the session to minimize its total bandwidth cost in the network, and therefore maximize the number of sessions the network can support. We propose both distributed and centralized routing and channel allocation algorithms to solve the problem. Simulation results show that our algorithms increase the maximum number of concurrent sessions that can be supported in the network, and also improve each session's performance with regard to spectrum mobility.