Investigations on PSO based task assignment algorithms for heterogeneous wireless sensor network

Modern heterogeneous wireless sensor nodes can be used to develop a wide plethora of sophisticated Wireless Sensor Network (WSN) applications. In a WSN, the nodes collaborate with each other to achieve the desired objectives by employing a task assignment algorithm. The majority of the existing WSN task assignment algorithms were designed for a homogeneous environment. However, the current trend of using heterogeneous nodes in WSN application warrants an elaborate investigations on the various factors influencing task assignment in heterogeneous environment. Extensive analysis on decisive factors such as node properties, WSN architecture, WSN application types were exhaustively carried out. Subsequently, a multi-objective based task assignment algorithm using Particle Swarm Optimization (PSO) was proposed. Various case studies on PSO by varying the fitness function and criteria weights were modelled and experimented through simulation to study the feasibility of achieving the desired objectives. The performance metrics such as energy consumption, response time and successful task assignment ratio were analyzed under different cases. Our investigations reveal that multi-objective based PSO outperforms its legacy counterpart in achieving the desired objectives with higher successful task assignment ratio in the heterogeneous environment.