Abstract

Wireless Power Transfer (WPT) technology is considered as a promising approach to make Wireless Rechargeable Sensor Network (WRSN) work perpetually. In WRSN, a vehicle exists, termed a mobile charger, which can move close to sensor nodes and charge them wirelessly. Due to the mobile charger’s limited traveling distance and speed, not every node that needs to be charged may be serviced in time. Thus, in such scenario, how to make a route plan for the mobile charger to determine which nodes should be charged first is a critical issue related to the network’s Quality of Service (QoS). In this paper, we propose a mobile charger’s scheduling algorithm to mitigate the data loss of network by considering the node’s criticality in connectivity and energy. First, we introduce a novel metric named criticality index to measure node’s connectivity contribution, which is computed as a summation of node’s neighbor dissimilarity. Furthermore, to reflect the node’s charging demand, an indicator called energy criticality is adopted to weight the criticality index, which is a normalized ratio of the node’s consumed energy to its total energy. Then, we formulate an optimization problem with the objective of maximizing total weighted criticality indexes of nodes to construct a charging tour, subject to the mobile charger’s traveling distance constraint. Due to the NP-hardness of the problem, a heuristic algorithm is proposed to solve it. The heuristic algorithm includes three steps, which is spanning tree growing, tour construction and tour improvement. Finally, we compare the proposed algorithm to the state-of-art scheduling algorithms. The obtained results demonstrate that the proposed algorithm is a promising one.

Highlights

  • Wireless Sensor Network (WSN) is widely used in many applications, such as environmental monitoring, target tracking, security surveillance, etc. [1]

  • In Wireless Rechargeable Sensor Network (WRSN), when the battery of a node is depleted, a wireless charging vehicle called a mobile charger, which is equipped with an energy transceiver and high capacity battery, can move close to the Sensors 2018, 18, 2223; doi:10.3390/s18072223

  • We study the impact of important parameters on the performance, including the number of nodes deployed, the charger’s traveling distance constraint, the charger’s traveling speed and the node’s received charging rate

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Summary

Introduction

Wireless Sensor Network (WSN) is widely used in many applications, such as environmental monitoring, target tracking, security surveillance, etc. [1]. Charging a number of nodes,time the and mobile charger has speed, not every nodestation whichfor needs to be charged is to serviced in time In such a scenario, it is limited necessary to return to the base refueling. Necessary to make a route plan for the mobile charger to determine which nodes should be charged first limited travel behaves distance. When a critical node node if it plays an irreplaceable role as a relay node in some routing paths. In order to decrease the risk of data loss, for the mobile to charger, charge as many criticality nodes include critical nodes as possible before batteries it is vital high to charge as many high criticality nodes include critical nodes as their possible beforeare depleted.

Example
Wireless Power Transfer Technology
Mobile Charger Schedule
Network Model and Charging Scheme
Network Model
Node’s Criticality Definition
Problem Formulation
A Heuristic Algorithm
Spanning Tree Growing
Tour Construction
Tour Improvement
Time Complexity Analysis
Simulation Evaluations
Simulation Environment
Property Analysis
Performance Comparison
Impact of Network Scale
Impact of Charger’s Traveling Distance Constraint
Impact
Impact of Charging Power
Findings
Conclusions and Future Work

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