An Energy Distance Aware Clustering Protocol with Dual Cluster Heads Using Niching Particle Swarm Optimization for Wireless Sensor Networks

Dexin Ma,Pengmin Xu

doi:10.1155/2015/849281

Abstract

Energy efficient utilization is an important criteria and factor that affects the design of wireless sensor networks (WSNs). In this literature, we propose an energy distance aware clustering protocol with Dual Cluster Heads using Niching Particle Swarm Optimization (DCH-NPSO). The protocol selects two cluster heads in each cluster, the Master Cluster Head (MCH) and the Slave Cluster Head (SCH), and the selection needs to consider the network state information carefully and deliberately. Simulation results show that the protocol we proposed can balance the energy dissipation and extend the network lifetime effectively.

Highlights

The application of wireless sensor networks (WSNs) becomes more wide in recent years; there are a large number of typical applications, such as environment surveillance and exploration, target tracking, and volcano activity monitoring [1]
We propose an energy distance aware clustering protocol with Dual Cluster Heads using Niching Particle Swarm Optimization (DCH-NPSO)
Each round contains three phase, a set-up phase uses DCH-NPSO to part the network into clusters and selects Master Cluster Head (MCH) and Slave Cluster Head (SCH) using Niching Particle swarm optimization (PSO), a steady phase when data collected and aggregated by the MCH, and a finish phase followed when data is transmitted to the BS (Base Station, called sink node); the steady phase should be longer than other phases to minimize the energy dissipation

Summary

Introduction

The application of WSNs becomes more wide in recent years; there are a large number of typical applications, such as environment surveillance and exploration, target tracking, and volcano activity monitoring [1]. As to implement on tiny wireless sensor nodes, an optimization method that needs moderate and even minimal computation efforts yet generates better results is needed. Particle swarm optimization has been used to resolve WSN issues such as clustering, localization, deployment, and data fusion [3]. A clustering particle swarm optimization [13] has been presented for dynamic optimization and employed a hierarchical clustering method to locate multiple optima for dynamic optimization problems. In this literature, we propose an energy distance aware clustering protocol with Dual Cluster Heads using Niching Particle Swarm Optimization (DCH-NPSO). The simulation results show that the protocol can balance the network loads, minimize the energy consumptions, and prolong the network lifespan of WSNs

System Model

DCH-NPSO Protocol

Simulation

Conclusion