Clustering in wireless sensor networks based on node ranking

The need for efficient optimization of network resources to prolong the life time of large-scale and dense deployments of Wireless Sensor Networks opened the door for researchers to study and produce efficient clustering techniques. Clustering has been proven to be an effective approach for organizing a large scale WSN into connected groups increasing the life time and the reliability of such networks. Distance of the nodes from the base station and inter-node distances can have a high influence on saving energy and prolonging the network life time. In this paper, a new algorithm based on node ranking is proposed. The proposed algorithm uses node ranking to elect cluster heads based on energy levels and positions of the nodes in reference to the base station used as a sink for gathered information. Also the algorithm provides a stronger coverage through maintaining a global knowledge at the base station which in turn ensures that all nodes are reachable through connected cluster heads. Since the BS calculates the number of rounds a cluster head can remain through in advance, this feature will have a great effect in prolonging the network life time as it reduces the amount of energy wasted on replacing cluster heads. The performance of this algorithm compared to other well-known algorithms will be presented.