An Energy-Efficient Coverage Enhancement Strategy for Wireless Sensor Networks Based on a Dynamic Partition Algorithm for Cellular Grids and an Improved Vampire Bat Optimizer.

Xiaoqiang Zhao,Zheng Guo,Yanpeng Cui,Zhanjun Hao

doi:10.3390/s20030619

Abstract

Sensor nodes perform missions based on the effectual invariable coverage of events, and it is commonly guaranteed by the determinate deployment for sensor nodes who deviate from the optimum site frequently. To reach the optimal coverage effect with the lowest costs is a primary goal of wireless sensor networks. In this paper, by splicing the sensing area optimally with cellular grids, the best deployment location for sensors and the required minimum number of them are revealed. The optimization problem of coverage rate and energy consumption is converted into a task assignment problem, and a dynamic partition algorithm for cellular grids is also proposed to improve the coverage effect when the number of sensors is variable. Furthermore, on the basis of solving the multi-objective problem of reducing and balancing the energy cost of sensors, the vampire bat optimizer is improved by introducing virtual bats and virtual preys, and finally solves the asymmetric assignment problem once the number of cellular grids is not equal to that of sensors. Simulation results indicate that the residual energy of sensors during redeployment is balanced notably by our strategy when compared to three other popular coverage-enhancement algorithms. Additionally, the total energy cost of sensor nodes and coverage rate can be optimized, and it also has a superior robustness when the number of nodes changes.

Highlights

With the rapid development of wireless communication technology, embedded computing technology, sensor technology, and microelectronic technology, wireless sensor networks (WSNs) which bring low-power, low-cost, distributed and self-organizing features to information perception have emerged at this historic moment
We compared the performance of virtual force algorithm (VFA), virtual force-directed particle swarm optimization (VFPSO), LGWO and of sensors
The performance of improved the vampire bat optimizer (IVBO) is insensitive to its parameters thanks to it transforming the sensor coverage enhancement problem to a task-assignment problem, it ensures an optimum coverage rate after the movements, which is the reason that final coverage rate Number (FCR) of VFA, LGWO and VFPSO are lower than that of IVBODCG in 200 simulation experiments as shown in Figures 14 and 15 and Tables 2 and 3

Summary

Introduction

With the rapid development of wireless communication technology, embedded computing technology, sensor technology, and microelectronic technology, wireless sensor networks (WSNs) which bring low-power, low-cost, distributed and self-organizing features to information perception have emerged at this historic moment. They have greatly changed the way humans interact with nature and established a bridge between the information and the physical world [1]. Coverage control and node deployment, which determine the ability to monitor the surrounding physical world and the quality of service (QoS) of WSNs, are one of the core issues in WSNs research. The mobile sensors are redeployed to enhance their coverage effect

Results

Discussion

Conclusion