A Two-Phase Coverage-Enhancing Algorithm for Hybrid Wireless Sensor Networks.

Qingguo Zhang,Mable Fok

doi:10.3390/s17010117

Abstract

Providing field coverage is a key task in many sensor network applications. In certain scenarios, the sensor field may have coverage holes due to random initial deployment of sensors; thus, the desired level of coverage cannot be achieved. A hybrid wireless sensor network is a cost-effective solution to this problem, which is achieved by repositioning a portion of the mobile sensors in the network to meet the network coverage requirement. This paper investigates how to redeploy mobile sensor nodes to improve network coverage in hybrid wireless sensor networks. We propose a two-phase coverage-enhancing algorithm for hybrid wireless sensor networks. In phase one, we use a differential evolution algorithm to compute the candidate’s target positions in the mobile sensor nodes that could potentially improve coverage. In the second phase, we use an optimization scheme on the candidate’s target positions calculated from phase one to reduce the accumulated potential moving distance of mobile sensors, such that the exact mobile sensor nodes that need to be moved as well as their final target positions can be determined. Experimental results show that the proposed algorithm provided significant improvement in terms of area coverage rate, average moving distance, area coverage–distance rate and the number of moved mobile sensors, when compare with other approaches.

Highlights

Wireless sensor networks (WSNs) are composed of a large number of sensor nodes that have limited resources such as energy, bandwidth, memory, and processing power
This paper focuses on the area coverage problem, where the main objective of the sensor network is to monitor an area and to solve the following area coverage problem in hybrid WSNs: Given a randomly deployed hybrid WSN with all sensors knowing their locations on a plane, determine where the mobile sensors should be moved such that the area coverage can be maximized, while incurring the least moving cost
To investigate the effect of the number of wireless sensor nodes to the optimization performance, a series of experiments in different hybrid WSNs with different numbers of sensor nodes are used to test against various algorithm including the proposed two-phase algorithm, genetic algorithm (GA) in [24], and particle swarm optimization (PSO) in [25]

Summary

Introduction

Wireless sensor networks (WSNs) are composed of a large number of sensor nodes that have limited resources such as energy, bandwidth, memory, and processing power. One key objective of these applications is to monitor a field of interest to detect movement, temperature changes, precipitation, and so forth, which depends on the coverage quality of the sensor network. The quality of coverage in static sensor is significantly affected by the initial deployment location of the sensors. Sensor deployment cannot be performed manually in most applications due to the remote or hostile working environments of WSNs. sensors are usually deployed by scattering them from an aircraft; the actual landing position cannot be controlled due to the existence of wind and obstacles such as trees and buildings. Even if a large number of redundant nodes are deployed, the desired

Methods

Results

Conclusion