Bio-inspired Algorithms for Autonomous Deployment and Localization of Sensor Nodes

Abstract--Optimal deployment and accurate localization of sensor nodes have a strong influence on the performance of a wireless sensor network (WSN). This paper considers real-time autonomous deployment of sensor nodes from an unmanned aerial vehicle (UAV). Such a deployment has importance, particularly in ad hoc WSNs, for emergency applications, such as disaster monitoring and battlefield surveillance. The objective is to deploy the nodes only in the terrains of interest, which are identified by segmentation of the images captured by a camera on board the UAV. Bioinspired algorithms, particle swarm optimization (PSO) and bacterial foraging algorithm (BFA), are presented in this paper for image segmentation. In addition, PSO and BFA are presented for distributed localization of the deployed nodes. Image segmentation for autonomous deployment and distributed localization are formulated as multidimensional optimization problems, and PSO and BFA are used as optimization tools. Comparisons...

• Type: Journal
• Year: 2010
• Where: TSMC
• Authors: Raghavendra V. Kulkarni, Ganesh K. Venayagamoorthy
• Keywords: Artificial Intelligence, Autonomous Deployment, Image Segmentation, Sensor Nodes, TSMC 2010