Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm

Optimum sensor node placement for wireless sensor network (WSN) in a monitored area is needed for cost-effective deployment. The location of sensor nodes must be able to offer maximum coverage and connectivity with minimum energy consumption. This paper proposes a sensor node placement approach that utilizes a new biologically inspired multi-objective optimization algorithm that imitates the behaviour of a territorial predator in marking their territories with their odours known as multi-objective territorial predator scent marking algorithm (MOTPSMA). The algorithm uses the maximum coverage and minimum energy consumption objective functions with subject to full connectivity. A simulation study has been carried out to compare the performance of the proposed algorithm with the multi-objective evolutionary algorithm with fuzzy dominance-based decomposition and an integer linear programming algorithm. Simulation results show that WSN deployed using the MOTPSMA sensor node placement algorithm outperforms the performance of the other two algorithms in terms of coverage, connectivity and energy usage.