Empirical Approach for Optimising Cumulative Network Lifetime in WSN with Hierarchical Clustering Technique Based on Fuzzy Logic

Empirical Approach for Optimising Cumulative Network Lifetime in WSN with Hierarchical Clustering Technique Based on Fuzzy Logic

Abstract

The area of wireless sensor network is shrouded with significant ranges of problems where majority of the prior research attempts were carried out to address energy conservation issues. The present manuscript introduces a novel technique called as ENLPL or Enhancing Network Lifetime Using Probabilistic Logic where the prime focus is laid on conserving the energy for large scale wireless sensor network. ENLPL presents design of inter and intra clustering approach using probability theory. It also laid emphasis on ensuring maximum participation of the sensor nodes in selection process of cluster-leader with an aid of maximum number of parameters. The outcome of the study was compared with conventional and standard hierarchical clustering algorithm (LEACH) to find ENLPL ensures better energy efficiency for large number of the sensor. With the adoption of the probabilistic reasoning technique, the simulation results shows that the proposed system maximizes the cumulative lifetime of the network, along with an efficient selection process of the cluster leader in every iteration.

References