A Clustering Algorithm for Wireless Sensor Network

In wireless sensor network the bad distribution for cluster head was not taken into account in traditional clustering algorithm such as LEACH algorithm. However the distribution uniformity for the cluster head in wireless sensor networks is very critical, for the better cluster head distribution could effectively save the communication cost and prolong the the lifespan of the network. The math programming approach that we use in this paper is based on a variation of a maximal expected covering location model due to Daskin. Daskin introduced a variant of the MCLP that considers the possibility that facilities may be unable to respond to demand at all times. The resultant model was labeled as MEXCLP (Maximum Expected Covering Location Problem). So we put forward the MEXCLP algorithm for clustering according to the greatest expectations of coverage principle, in this algorithm the cluster head was taken regarded as the provider of services, the cluster head could provide service to the member nodes in the cluster. The algorithm considers the process of service failure (link failure, and so on), and it is based on the assumption of probability of the services failure, a reasonable choice through the head cluster node enables network nodes be served with the largest request number. From the simulation results can be see that the MEXCLP algorithm is more uniformed in finding head cluster, and under the same failure rate circumstances, MEXCLP algorithm may provide more efficient service and consume less energy than the LEACH algorithm. So this clustering algorithm could effectively and efficiently be suitable to the wireless sensor network and provide more reliable service for the sensor nodes in the cluster.