An Energy-Effective Clustering Algorithm for Multilevel Energy Heterogeneous Wireless Sensor Networks

Clustering provides an effective way for data gathering in wireless sensor networks. In practice applications, either the difference of energy consumed by sensor nodes or node redeployment leads to the energy heterogeneous networks. This paper proposes a new distributed Low-Energy node Protection Time-driven Clustering algorithm (LEPTC) for heterogeneous wireless sensor networks, in which nodes are initialized with different energy levels. This new approach aims at guaranteeing more uniform energy consumption of the nodes and prolonging their lifetime. In LEPTC, cluster head selection is primarily based on the residual energy ratio between a node and its neighboring node with lowest energy. As a result, a node with higher residual energy around the low-energy node will produce a shorter time for cluster head competition and hence have more chance to become a cluster head. So LEPTC can better handle the heterogeneous energy capacities. Moreover, LEPTC adopts a multi-hop data transmission manner for the "forced cluster heads". Simulation results show that LEPTC outperforms some existing clustering methods in terms of the network lifetime and the network data capacity in energy heterogeneous networks.