Hybrid Approach for Sensor Deployment in Wsn

Wireless Sensor Networks (WSNs) consists of arbitrarily placed tiny sensors which monitor the target field. Every location of the target field is said to be with at least one sensor. The sensors must be deployed in such a way that every sensor is efficiently used to monitor the target field with less coverage loss. Glow worm Swarm Optimization (GSO) technique is swarm intelligence based technique, which depends on the behaviour of glow worms (also called as lightning bugs or fireflies). In sensor node deployment optimization, GSO performs very well in terms of coverage and is used to achieve greater coverage with less sensor nodes in the network. The solutions obtained by hybrid approach which is based on GSO and Bioluminescent Swarm Optimization (BiSO) are better than the best solutions obtained by an efficient Glow worm Swarm optimizer alone. This approach is a free from differential equations and is a very efficient evolutionary algorithm. Non-Stochastic adaptive step-size movement strategy is implemented which is derived from GSO and BiSO. On the basis of considering dynamic deployment in WSNs, simulation results show that the hybrid approach yields greater coverage than the existing GSO technique.