Energy Efficient Recursive Clustering and Gathering in Big Data for Wireless Sensor Networks

Abstract

Big data is one of the emerging technology in Wireless Sensor Networks (WSN). Gathering of data is the biggest challenge for implementing big data in WSN. In WSN, the frequent information communications between the nodes are inevitable. Moreover, the long distance communication between the nodes in the network lead to reduction in the lifetime of the nodes. In order to reduce communication distance between the nodes and to efficiently gather large amount of data. Energy Efficient Recursive Clustering and Gathering for big data in WSN is proposed. In proposed algorithm, the grid area will be divided into zones. The zones are divided by finding the minimum and maximum X and Y from the nodes location and distribution of nodes in the network. In each zone, clusters are formed in recursive manner. After the clusters are formed in recursive manner, for every cluster, the Cluster Administrator are elected based on the maximum energy among the nodes in the cluster. Once the Cluster Administrators are elected, the Cluster Administrator which has the maximum energy in the Zone, will be elected as a Cluster Head. The Cluster Head only send the information for a particular zone. Energy consumption will be reduced as the cluster head only sends the information to the base station, instead of every nodes in the zone. The localization algorithm based on Received Signal Strength Indicator (RSSI) and multi hop routing is performed to reduce end-to-end delay in the network. The simulated results show that the proposed algorithm gathers large amount of data with low energy consumption than the existing algorithm.