Chain Based Leader Selection using Neural Network in Wireless Sensor Networks protocols

In wireless sensor networks (WSNs), selecting a chain leader is a critical issue. In this paper, we present a novel method for selecting chain leaders in a chain-based routing protocols that utilizes a Neural Network (NN). Our proposed method is applicable to any chain-based routing protocol, such as PEGASIS (Power-Efficient Gathering in Sensor Information Systems) [6], CBERP (Cluster Based Energy Efficient Routing Protocol) [15], CCM (Chain-Cluster Based Mixed Routing Protocol) [14], CCBRP (Chain-Chain Based Routing Protocol) [18], and others. To validate our claim that our method can be applied to any chain-based routing protocol, we checked it on two of the most well-known protocols, PEGASIS (the original chain-based routing protocol) and CCBRP. It is well recognized that energy consumption is a critical issue for all WSNs. Our proposed methodology uses the Neural Network as a tool to select chain leaders based on the residual energy of each network member node. The simulation results show that the use of our proposed method improved the performance of both PEGASIS and CCBRP in terms of consumed energy and network lifetime.