Mobile Multi-Sink Nodes Path Planning Algorithm Concerned With Energy Balance in Wireless Sensor Networks

Supeng Sun,Xin Feng,Jianping Zhao,Jing Zhang,Jiaqi Luo

doi:10.1109/access.2019.2929583

Abstract

In order to relieve the problem of unbalanced energy consumption of sensor nodes near the base station in the wireless sensor network, this paper proposes a mobile multi-sink nodes path planning algorithm with energy balance (hexHPSO). An optimization model is established by considering the energy consumption of each group, network lifetime, and movement path of the mobile sink nodes. Meanwhile, a hybrid positive and negative particle swarm optimization algorithm (HPNPSOA) is proposed to solve the optimization model to obtain a path with optimal grid traversal order and optimal parking position. Compared with the DOSM algorithm, GLRM algorithm, and RWM algorithm, the hexHPSO algorithm improves the network lifetime by 68%. The experimental results show that the hexHPSO algorithm can effectively balance the energy consumption, alleviate hotspot phenomenon, and extend the network lifetime.

Highlights

The many-to-one transmission mode results in consuming a large amount of energy near the base station in wireless sensor networks which makes many nodes die prematurely and shortens the network lifetime
THE DETAIL OF HPNPSOA For the general TSP problem, it can be solved by the hybrid particle swarm optimization algorithm (HPSOA) [22]
This paper proposes a hybrid positive and negative particle swarm optimization algorithm (HPNPSOA) to solve this optimization model

Summary

INTRODUCTION

The many-to-one transmission mode results in consuming a large amount of energy near the base station in wireless sensor networks which makes many nodes die prematurely and shortens the network lifetime. Algorithms proposed in [16], [17] only consider the optimization of single factor (delay, path length) in the path planning of mobile sink nodes, do not consider the combination optimization problem that include energy consumption of sensor nodes and the network lifetime. In [18], the proposed algorithm builds the network into multiple circles with different communication ranges according to each sensor node at first, mobile sink node moves to the communication range of each sensor node to collect data, VOLUME 7, 2019 builds a model of energy consumption and movement path, and uses mixed immunity particle swarm algorithm to plan the path. DTSP in formula (16) represents the entire path length, which is the sum of paths of all mobile sink node

THE DETAIL OF HPNPSOA

Findings

CONCLUSIONS