An Adaptive Distributed Clustering with Topology Control approach for Sensor Networks

Abstract

Adaptive distributed clustering with topology control is added in the sensor network for organizing the sensor nodes in an effective approach and energy consumption. In a cluster, effective inter-and intra-node communication is essential for the workload sense of balance among the nodes, updating new nodes in the network, increasing the network lifetime and valuable resource exploitation. This mechanism is suitable for streaming of data, scalable to huge dimension networks, detachment of the sensor nodes in to level headed sets faster and extensively speeds up the communication among nodes compared to the adaptive and optimal distributed clustering algorithm. This proposal includes the least connection algorithm which directs link connections to the cluster head with the least number of established connections among the nodes. Simulation results show that the performance of adaptive distributed clustering provides higher throughput and energy consumption.