Particle Swarm Optimization for the Deployment of Directional Sensors

被引:2
|
作者
Singh, Pankaj [1 ]
Mini, S. [1 ]
Sabale, Ketan [1 ]
机构
[1] Natl Inst Technol Goa, Farmagudi, Goa, India
关键词
Wireless sensor networks; Directional sensor networks; Sensor deployment; Particle swarm optimization; COVERAGE;
D O I
10.1007/978-3-319-48959-9_15
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Directional sensors are a special class of sensors that have special characteristics, such as the angle of sensing. Hence the techniques or methods that are used to solve problems in traditional disk-based sensing models may not be applicable to directional sensor networks. Random deployment of directional sensor nodes usually fails where the number of sensors are limited or have less sensing capability. This paper addresses coverage enhancement of applications that use directional sensor nodes. We assume that the number of directional sensor nodes are less than the number of objects to be covered in the region. The main aim is to identify the optimal/near optimal deployment locations of the directional sensor nodes such that the coverage is maximized. We use Particle Swarm Optimization (PSO) algorithm to compute the deployment locations of the nodes. The experimental results reveal that PSO is a promising method to solve this problem.
引用
收藏
页码:167 / 175
页数:9
相关论文
共 50 条
  • [31] An improved dynamic deployment method for wireless sensor network based on multi-swarm particle swarm optimization
    Qingjian Ni
    Huimin Du
    Qianqian Pan
    Cen Cao
    Yuqing Zhai
    [J]. Natural Computing, 2017, 16 : 5 - 13
  • [32] An improved dynamic deployment method for wireless sensor network based on multi-swarm particle swarm optimization
    Ni, Qingjian
    Du, Huimin
    Pan, Qianqian
    Cao, Cen
    Zhai, Yuqing
    [J]. NATURAL COMPUTING, 2017, 16 (01) : 5 - 13
  • [33] Improved AP Deployment Optimization Scheme Based on Multi-objective Particle Swarm Optimization Algorithm
    Kong, Zhengyu
    Wu, Duanpo
    Jin, Xinyu
    Cen, Shuwei
    Dong, Fang
    [J]. KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, 2021, 15 (04): : 1568 - 1589
  • [34] Underwater Wireless Sensor Network Deployment Based on Chaotic Particle Swarm Optimization Algorithm
    Su, Shaojuan
    Wang, Tianlin
    [J]. INTERNATIONAL JOURNAL OF ONLINE ENGINEERING, 2015, 11 (01) : 25 - 28
  • [35] The Optimization Methods for Wireless Sensor Network Nodes Deployment Based on Hybrid Particle Swarm
    Li, Yan
    Dong, Honghui
    Jia, Limin
    Tang, Junqing
    [J]. PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON ELECTRICAL AND INFORMATION TECHNOLOGIES FOR RAIL TRANSPORTATION: TRANSPORTATION, 2016, 378 : 1 - 8
  • [36] Hovering Swarm Particle Swarm Optimization
    Karim, Aasam Abdul
    Isa, Nor Ashidi Mat
    Lim, Wei Hong
    [J]. IEEE ACCESS, 2021, 9 : 115719 - 115749
  • [37] Energy Efficient Deployment of VLC-Enabled UAV Using Particle Swarm Optimization
    Ibraiwish, Hussam
    Eltokhey, Mahmoud Wafik
    Alouini, Mohamed-Slim
    [J]. IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY, 2024, 5 : 553 - 565
  • [38] Efficient base station deployment in specialized regions with splitting particle swarm optimization algorithm
    Shen, Jiaying
    Zhu, Donglin
    Li, Rui
    Zhu, Xingyun
    Zhang, Yuemai
    Li, Weijie
    Zhou, Changjun
    Zhang, Jun
    Cheng, Shi
    [J]. WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, 2024, 27 (04):
  • [39] Particle swarm optimization
    Venter, G
    Sobieszczanski-Sobieski, J
    [J]. AIAA JOURNAL, 2003, 41 (08) : 1583 - 1589
  • [40] Particle Swarm Optimization in Swarm Robotics
    Turkler, Levent
    Akkan, L. Ozlem
    Akkan, Taner
    [J]. 2ND INTERNATIONAL CONGRESS ON HUMAN-COMPUTER INTERACTION, OPTIMIZATION AND ROBOTIC APPLICATIONS (HORA 2020), 2020, : 305 - 310