Energy efficient aggregation in wireless sensor networks for multiple base stations

Abstract

Data aggregation is essential for wireless sensor networks (WSN) where energy resources are limited. Due to scarce energy resources, construction of data aggregation tree in WSN from group of source nodes to sink nodes with less energy consumption is challenging. In this work, we propose a method to determine the aggregation tree with less energy consumption using Artificial Bee Colony (ABC) algorithm, which is a swarm intelligence technique. We compute the fitness (energy consumption of whole network) by considering multiple algorithms in the same network and then evolving the solution until fitness value is minimum. Our preliminary results suggest that, under investigated scenarios, the usage of ABC algorithm for aggregation in WSN with multiple base stations can achieve energy savings over Shortest path tree data aggregation and Ant colony data aggregation with multiple base stations. © 2013 Springer International Publishing.