Prolonging Network Survivability and Optimizing Energy Consumption in Heterogeneous Wireless Sensor Networks

Abstract

WSNs embedded device can be extended to a wide range of implementation in reality. Clustering is efficient way to lessen the energy utilization and improve WSN's lifespan. To improvise network lifespan numerous clustering approaches, implement various parameters for election of CH. An effective clustering algorithm depends upon the number of factors such as number of CHs, uniform cluster size, CHs distribution, energy of the CHs etc. In our research we strengthen our methodology for election of cluster head in HWSN depending on multiple node parameters such as distance, density and residual energy. This paper aims to optimize energy and improve network with Energy Balanced Cluster Technique (EBCT). In our research we reformulated for probability estimation to identify the CHs in each round characterized by node parameters: distance, density, residual energy and node dormancy mechanism. Mathematical analysis and simulations show the proposed method extends the service life by around 8% to 53% relative to the other protocols and optimizes energy utilization of HWSNs.