Extending the Lifetime of Wireless Sensor Networks with Threshold Sensitive Stochastic Election Approach

Wireless sensor networks are composed of a broad array of independent sensors called nodes. These nodes are inexpensive and are used in data gathering usually in hostile environments. They collect data physical or environmental conditions, such as temperature, pressure, etc. And send it to a base station. They are limited in efficiency, secure routing, load sharing, etc. To overcome these issues clustering is performed in WSN, which partitions the network into groups. Each group selects a cluster head which gathers data from all the nodes and sends it to the base station. These groups head are selected using various algorithms which are based on residual energy, distance, etc. The proposed algorithm suggests the usage of a stochastic election approach to effectuate the improvement in load balancing of clusters in wireless sensor networks which also improves the network lifetime. The proposed system is a modified version of the SEARCH algorithm which is adapted with data thresholding to increase the network lifetime and remove redundancy of the data sent. The simulation results show that the proposed approach is more efficient than other distributed algorithms. This technique can be easily extended to large-scale wireless sensor networks.