Genetic simulated annealing-based coverage-enhancing algorithm for multimedia directional sensor networks

被引:9
|
作者
Zhang, Ke [1 ]
Duan, Chang [1 ]
Jia, Haitao [1 ]
机构
[1] Univ Elect Sci & Technol China, Res Inst Elect Sci & Technol, Chengdu 611731, Sichuan, Peoples R China
关键词
multimedia; directional sensor networks; coverage-enhancing; genetic algorithm; simulated annealing algorithm; MACHINES;
D O I
10.1002/dac.2737
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Multimedia directional sensor network is one kind of directional sensing systems, whose coverage scheme is quite different from the omnidirectional sensing system. And it is often used in atrocious environmental surveillance, such as nuclear contaminative areas, where people can hardly arrive. In this paper, a genetic simulated annealing-based coverage-enhancing algorithm (GSACEA) is proposed as a coverage-enhancing method in multimedia directional sensor networks. Firstly, GSACEA combines the genetic algorithm and simulated annealing algorithm into an algorithm with new architecture. Then, the proposed GSACEA is applied for the purpose of coverage-enhancing in the case of directional sensor networks with rotational direction-adjustable model. Finally, after series actions of genetic simulated annealing, the proposed method can find the approximate solution to the best area coverage rate. And according to the results of simulations, which compared the proposed method with several other classic coverage-enhancing methods in directional sensor networks, it could be concluded that GSACEA can achieve the highest area coverage rate of directional sensor networks and reduce the iterative computing times simultaneously. Copyright (c) 2014 John Wiley & Sons, Ltd.
引用
收藏
页码:1598 / 1609
页数:12
相关论文
共 50 条
  • [21] Coverage-Enhancing algorithm for video sensor network based on improved particle swarm optimization
    Fu, Xiang
    Zeng, Jiexian
    [J]. PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS RESEARCH AND MECHATRONICS ENGINEERING, 2015, 121 : 446 - 450
  • [22] A simulated annealing-based algorithm for selecting balanced samples
    Benedetti, Roberto
    Dickson, Maria Michela
    Espa, Giuseppe
    Pantalone, Francesco
    Piersimoni, Federica
    [J]. COMPUTATIONAL STATISTICS, 2022, 37 (01) : 491 - 505
  • [23] A simulated annealing-based multiobjective optimization algorithm: AMOSA
    Bandyopadhyay, Sanghamitra
    Saha, Sriparna
    Maulik, Ujjwal
    Deb, Kalyanmoy
    [J]. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2008, 12 (03) : 269 - 283
  • [24] A simulated annealing-based algorithm for selecting balanced samples
    Roberto Benedetti
    Maria Michela Dickson
    Giuseppe Espa
    Francesco Pantalone
    Federica Piersimoni
    [J]. Computational Statistics, 2022, 37 : 491 - 505
  • [25] A simulated annealing-based optimization algorithm for process planning
    Ma, GH
    Zhang, YF
    Nee, AYC
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2000, 38 (12) : 2671 - 2687
  • [26] Virtual potential field and covering factor based coverage-enhancing algorithm for three-dimensional wireless sensor networks
    Huang, Jun-Jie
    Sun, Li-Juan
    Wang, Ru-Chuan
    Huang, Hai-Ping
    [J]. Tongxin Xuebao/Journal on Communications, 2010, 31 (9 A): : 16 - 21
  • [27] A simulated annealing-based learning algorithm for Boolean DNF
    Albrecht, A
    Steinhöfel, K
    [J]. ADVANCED TOPICS IN ARTIFICIAL INTELLIGENCE, 1999, 1747 : 193 - 204
  • [28] Priority-based target coverage in directional sensor networks using a genetic algorithm
    Wang, Jian
    Niu, Changyong
    Shen, Ruimin
    [J]. COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2009, 57 (11-12) : 1915 - 1922
  • [29] A Simulated Annealing-Based Algorithm for Traveling Salesman Problem
    郭茂祖
    陈彬
    洪家荣
    [J]. Journal of Harbin Institute of Technology(New series), 1997, (04) : 35 - 38
  • [30] Evolving artificial neural networks using simulated annealing-based hybrid genetic algorithms
    Shi, Huawang
    Li, Wanqing
    [J]. Journal of Software, 2010, 5 (04) : 353 - 360