Cross-layer energy efficient clustering for heterogeneous wireless sensor networks with renewable energy sources

Abstract

The clustering Algorithm is a kind of key technique used to reduce energy consumption. It can increase the scalability and lifetime of the networks. Energy-efficient clustering algorithm should be designed for the characteristic of heterogeneous wireless sensor networks. We propose and evaluate a new cross-layer energy efficient clustering (CLEEC) algorithm for heterogeneous wireless sensor networks with renewable energy source. In CLEEC, the cluster heads are elected by probabilities based on cross-layer optimal estimation, considering energy replenishment. The cross-layer optimal estimation uses cross-layer information, such as energy and replenishment rate, to theoretically compute the election probabilities. Finally, the simulation results demonstrate that our clustering approach outperforms current important clustering algorithms in the efficiency of prolonging the network lifetime.