Broadcasting in cognitive wireless mesh networks with dynamic channel conditions

Recently, a variant of the popular wireless mesh network (WMN) technology, in which nodes communicate over multi-hop wireless links, has been proposed to address the problem of wireless interference and the scarcity of wireless spectrum. Such networks, which we shall call cognitive-radio wireless mesh networks (CWMN), can dynamically adapt network parameters according to existing conditions of the wireless channel. Such networks can also spot spectrum holes (or white-spaces, which are licensed spectrum slots currently not being used) and utilize them without causing interference to the incumbent users. There are numerous broadcast-oriented applications in WMNs, and in CWMNs by extension, that are sensitive to end-to-end delay. The inherent susceptibility of wireless links to interference, and the time-varying nature of wireless link´s quality, makes the design of efficient broadcasting algorithms for WMNs especially challenging. While minimum-latency broadcasting algorithms have been proposed in literature, they do not take into account the time-varying nature of wireless links in which channels may become unavailable due to interference (or, appearance of an incumbent user). Therefore, using the existing algorithms in CWMNs would necessitate expensive reconstruction of the tree in case of significant change in wireless topology due to interference or appearance of primary user. In this work, we propose a healing algorithm that addresses the problem of time-varying quality of wireless links and avoids expensive reconstruction of the entire tree by fixing the broken tree in a localized and decentralized manner. Simulation results show that our local healing algorithm improves both the broadcast latency and connectivity ratio (in face of interference) as compared to the approach of global reconstruction of trees.