Dynamic Multi-level Hierarchal Clustering Approach for Wireless Sensor Networks

Wireless sensor networks have the problem of lifetime and scalability. To increase lifetime and scalability it’s necessary to have control over topology of the network. Dynamic clustering with adaptive feature is the best way to achieve the above. In this paper we propose a dynamic multi-level hierarchal clustering (DMH) approach for sensor networks. The proposed approach will create a dynamic system which can vary topology architecture according to traffic patterns. This approach can decide size of cluster, nodes in a cluster and level of hierarchy of a cluster and will vary according to state of the system. In this approach for clustering we use nodes having multiple energy level for energy efficient clustering and cluster heads are selected periodically based on different attributes (i.e. residual energy, node degree etc) but unlike previous approaches here we use mutual negotiation between nodes as a criteria for cluster formation. Also here we used dynamic adaptive level of hierarchy according to the traffic pattern and use the highest level of hierarchy for routing of aggregated data to the base station.