Exploiting Multiple Channels for Low Latency and Semireliable Broadcasting in Cognitive Wireless Sensor Networks

Abstract

In Wireless Sensor Networks (WSNs), disaster management is a crucial issue that focuses on disaster relief and recovery. Mobile sensor nodes support disaster relief and recovery by means of real-time bidirectional communication. For its high data rate requirement, IEEE 802.11 specification can be used for the radio interface of sensor nodes, and the nodes can be equipped with multiple 802.11 radios to utilize multiple channels and link data rates. Channel assignment algorithms can be applied in cognitive radio enabled networks which performs dynamic channel configuration for utilizing multiple channels. For efficient and semireliable broadcast in cognitive radio WSNs, we focus on reducing broadcast latency and achieving 100% delivery percentage. To realize these goals, in this study, we present our design for a novel Channel Assignment Algorithm for a Collision-Reduced Broadcast Tree (CA-CBT). Fundamentally, CA-CBT builds a broadcast tree and then uses several heuristic procedures to allocate collision-free channels to links on the tree. If CA-CBT fails to allocate collision-free channels due to a limited number of available channels, it allocates non-collision-free channels with the smallest number of interfering nodes. Through extensive simulations, we demonstrated that CA-CBT supports lower broadcast latency and higher delivery percentages compared with existing broadcast algorithms.