An Adaptive, Scalable and Self-Healing Sensor Network Architecture for Autonomous Coastal Environmental Monitoring

Wireless sensor networks (WSNs) are key technology enablers for the current and near future security and surveillance systems. In order to build realtime, multi-modal, high resolution monitoring in those systems, WSN applications need to address critical challenges such as autonomy, scalability, self-healing and simplicity. Based on the observation that various biological systems have developed mechanisms to meet these challenges, BiSNET (Biologically-inspired architecture for Sensor NETworks) implements key biological mechanisms such as energy exchange, pheromone emission, replication and migration to design WSN applications. This paper describes major system components in BiSNET and shows recent simulation results to evaluate BiSNET for oil spill detection in the coastal environment. Simulation results show that BiSNET allows sensor nodes to autonomously adapt their node states and data transmission according to dynamic changes in node/network conditions, retain their power efficiency against the increase of network size (up to 600 nodes), and collectively self-heal (i.e., detect and eliminate) false positive sensor data. Thanks to a set of simple biologically-inspired mechanisms, the BiSNET runtime is implemented lightweight.