Traffic Based Clustering in Wireless Sensor Network

Abstract

To increase the lifetime and scalability of a wireless sensor network (WSN) it is necessary to have control over topology of the network. Dynamic clustering is one way to achieve the above defined objective. In this paper, we propose a hierarchal clustering approach to adapt the size of clusters and number of hierarchal level in accordance with the traffic patterns and density of sensor nodes deployed in a given area of interest. As all the traffic is directed to the base station, the traffic load on the cluster heads in the vicinity of a base station is far more as compared to distant cluster heads. This may result in draining out of proximity cluster heads sooner than other cluster heads. The network would fail even though most of the distant nodes have sufficient energy. A bottleneck is created near the base station. The proposed algorithm of hierarchical clustering with variable cluster size based on its distance from the base station endeavors to balance the inter-cluster traffic so that energy depletion in cluster-heads is uniformly distributed. Variable cluster size is also able to balance the intra-cluster traffic. Simulation results show that load balancing through hierarchical variable size approach is able to enhance the network lifetime.