Cluster Based Energy Efficient Routing Protocol Using ANT Colony Optimization and Breadth First Search

This paper presents an algorithm to choose optimal path for data delivery for continuous monitoring of vital signs of patients in Body Area Network (BAN) in hospital indoor environments where a large number of patients exist and the traffic generated on the path rapidly changes over time. The methodology for finding the optimal path includes a meta-heuristic that combines ANT Colony Optimization (ACO) using Clustering. We propose a ACOBAN Clustering for monitoring BAN data and propose a method to improve network life, energy, load balancing on the overall network. Since traffic generated by BANs on the network changes with time, so the optimal path is important in Wireless Body Area Network. Our algorithm ensures network connectivity by using a mechanism of modified Cluster Head rotation process level by level and using breadth first search algorithm which avoids trapping during exploration. In the current work, we implemented ACO method and done experimental results on OMNeT++ to prove that the proposed method can find a better solution than conventional methods. (C) 2016 The Authors. Published by Elsevier B.V.