An Effective Data Gathering Scheme in Heterogeneous Energy Wireless Sensor Networks

Abstract

Data gathering is a major function of many applications in wireless sensor networks (WSNs). In real world applications, it is unrealistic to guarantee all sensors have the same energy because they have different energy consumption. Moreover, sensor redeployment also results in the heterogeneous energy capacities. In this paper, An effective data gathering scheme for heterogeneous energy WSNs (EDGA) is proposed. EDGA achieves a good performance in terms of lifetime by minimizing energy consumption for in-network communications and balancing the energy load. EDGA is based on weighted election probabilities of each node to become a cluster head, which can better handle the heterogeneous energy capacities. Moreover, EDGA adopt a simple but efficient method to solve the area coverage problem in a cluster range, namely intra-cluster coverage. Finally, the simulation results demonstrate that the proposed EDGA significantly outperforms LEACH, HEED in terms of network lifetime and the amount of data gathered in the heterogeneous energy network.