Maximal Weighted Coverage Deployment of UAV-Enabled Rechargeable Visual Sensor Networks

Xiaojian Zhu, Mengchu Zhou

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Due to the generation and transmission of video data, the high energy consumption rates of wireless nodes result in short lifetime of a visual sensor network, which has been commonly deployed in 3D space. In many applications, lots of targets need to be covered, but the budgets of both deployment and maintenance are limited. Therefore, how to maximize total weighted target coverage while prolonging network lifetime is of great significance. This work investigates the maximum weighted target coverage deployment of a rechargeable visual sensor network charged by an unmanned aerial vehicle (UAV) in 3D space, which should ensure network permanence and satisfy the budgets of both deployment and maintenance. In this problem, since UAV has a limited energy capacity, it is allowed to return to the depot for energy replenishment more than once in each charging period of wireless nodes so as to increase target coverage. After formulating this problem as a mixed integer nonlinear program, this work proposes a greedy heuristic and a particle swarm optimizer to approximately solve this NP-hard problem. Extensive simulation results reveal that the latter can deliver a better solution despite consuming more time than the former.

Original languageEnglish (US)
Pages (from-to)11293-11307
Number of pages15
JournalIEEE Transactions on Intelligent Transportation Systems
Volume24
Issue number10
DOIs
StatePublished - Oct 1 2023

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Automotive Engineering
  • Computer Science Applications

Keywords

  • 3D coverage
  • UAV scheduling
  • Visual sensor networks
  • node deployment
  • wireless charging

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