+Advanced Search
Home > Archive>Volume 45, Issue 15, 2022 >48-56
PDF HTML XML Export Cite reminder
Multi-objective coverage optimization of WSN based on improved sparrow search algorithm
CSTR:
[cstr]
Author:
Affiliation:

1. Chongqing Key Laboratory of Geological Environment Monitoring and Disaster Early Warning in Three Gorges Reservoir Area, Chongqing Three Gorges University, Chongqing 404120, China; 2. Key Laboratory of Intelligent Information Processing and Control, Chongqing Three Gorges University, Chongqing 404120, China; 3. Internet of Things and Intelligent Control Technology Chongqing Engineering Research Center, Chongqing Three Gorges University, Chongqing 404120, China; 4. School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China

Clc Number:

TP393

  • Article
    • | |
  • Metrics
    • |
  • Reference
    • |
  • Related
    • |
  • Cited by
    • | |
  • Comments
    Abstract:

    The randomly deployed nodes will lead to the insufficient coverage in Wireless Sensor Networks (WSNs). To solve this problem, an improved sparrow search algorithm - increment of coverage ratio (ISSA-ICR) was proposed. Firstly, to solve the problem that the producer converging to the origin, ISSA modified the location update method of the producer to avoid the algorithm falling into the local optimal solution; Secondly, to balance the global and local search ability of the algorithm, t-distribution disturbance with the number of iterations as the degree of freedom parameter and the dynamic adjustment strategy of the number of producers- scroungers were proposed; Thirdly, random regression cross-border processing strategy was adopted to solve the problem of individual cross-border relocation, and the candidate location of nodes to be deployed was determined; Finally, the node scheduling optimization model was constructed based on ICR strategy to determine the final deployment location. The simulation results show that compared with sparrow search algorithm, standard particle swarm optimization and adaptive virtual force disturbance sparrow search algorithm, ISSA-ICR can respectively improve 4.96%, 8.81% and 3.84% coverage ratio compared with the three algorithms, meanwhile reducing the nodes moving distance.

    Reference
    Related
    Cited by
Get Citation

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Online: April 08,2024
Article QR Code
You are the first Visitors
Governing Body：Beijing Electronic Holding Co., LTD
Organizer：Beijing Radio Technology Research Institute
Address：No.79 Beiheyan Street, Dongcheng District, Beijing China, 100009
Phone：13810562337
Electric Measurement Technology ® 2025 All Rights Reserved