An Adaptive Clustering Algorithm with Power Control in Wireless Sensor Networks

We propose an adaptive clustering algorithm with power control, ACA-PC, that chooses adaptive clusters and controls transmission power levels in order to minimize the total energy consumption of the sensor networks and maximize the amount of transmission data. Our core concepts are zone division and dynamic power control. A sensor network is divided into n zones based on geographical information. A large number of nodes bring about collision of data transmission. According to node density, a zone can be divided into two sub-zones or merged with other zone. The close neighbor nodes are grouped by a cluster in its zone. Therefore, we control the transmission power level of the common nodes in the same cluster to avoid collision with other clusters. Using network simulator (NS-2), we verify that ACA-PC can conserve the energy of sensors and prolong the lifetime of sensor networks better than other proposed algorithms.