Data Aggregation in Wireless Sensor Network Using Shuffled Frog Algorithm

Abstract

Wireless Sensor Networks (WSNs) is made of numerous autonomous sensors forming a wireless network and cooperating with one another to transmit sensed data to a base station. With the advent of biomedical sensors, healthcare application for monitoring of vital body signs of patients is developing rapidly wherein all sensors cooperatively send data to the central server. The network routing protocols aims to reduce energy consumption and prolonging network life. Clustering is an important method to prolong network life in WSNs. It involves sensor nodes grouping into clusters and selecting Cluster Heads (CHs). Cluster Heads aggregate data its group and forward accumulated data to base station resulting in a higher energy spend. A big WSN challenge is selecting suitable CHs as they dissipate more energy compared to regular nodes in the network. A popular clustering protocol, LEACH offsets this by probabilistically rotating CHs role among nodes. Nevertheless, network performance may not be optimal if the CHs are not selected appropriately. This paper presents a shuffled frog meta-heuristic algorithm for CHs selection. The proposed method chooses CH based on energy remaining in the nodes. Simulation results shows the proposed technique to outperform LEACH and Genetic Algorithm based methods in terms of Quality of Service.