Cluster based comb needle model using ISO data algorithm in the random wireless sensor network

This paper proposes the cluster based comb needle model using ISO data algorithm in the random network for the making efficient data aggregation with the help of weighted compressive sensing method in the random network for estimating the suitable network in order to minimize the energy consumption in the wireless sensor network. It makes the comparative analysis of the proposed cluster based comb needle model with the extended comb needle model for determining best comb needle model in the random network in terms of minimum energy consumption, communication cost, packet delivery ratio, throughput and delay. Moreover, it improves the lifespan of the network. The proposed method uses the ISO data clustering algorithm to produce the best clustering scheme with energy efficiency. Thus the experimental results for cluster based comb needle model in ISO data algorithm in random networks are executed using NS2 stimulator.