Performance analysis for lifetime improvement of a regression based clustered network through cluster member allocation and secondary cluster head selection in a distributed WSN

Abstract

Emerging boundless applications of the wireless sensor network considers the coverage as the biggest issue in yielding a good quality of service. The term coverage is strongly correlated with the Lifetime of the network. Improving the network lifetime therefore enhances the sensing task of any network. The work takes up two techniques for improving the lifetime of the linear iterative regression based clustered network. As the energy of the cluster head drains below a threshold due to the traffic carried, the cluster member of the dead heading node can be allocated to some existing eligible cluster heads in the network so that the data sensed by these nodes can still be communicated to the sink. Alternately the allocation of secondary cluster head can be done for the aggregation of data which serves for improvement in lifetime of the network. With exhaustive simulation and evaluated results the performance of the two schemes are compared using throughput, Network lifetime and residual energy and it shows that the secondary cluster head allocation scheme is better in performance improvement of the network with the lifetime improvement of 22.8% and throughput improvement of 18.6% as compared to that of the cluster member allocation scheme.