Distributed Center and Coverage Region Estimation in Wireless Sensor Networks Using Diffusion Adaptation

被引:0
作者
Zhang, Sai [1 ]
Tepedelenlioglu, Cihan [1 ]
Spanias, Andreas [1 ]
机构
[1] Arizona State Univ, Sch Elect Comp & Energy Engn, SenSIP Ctr, Tempe, AZ 85287 USA
来源
2017 FIFTY-FIRST ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS | 2017年
关键词
Wireless Sensor Networks; Network Center; Network Radius; Soft-max; Max Consensus; Diffusion Adaptation; MAX-CONSENSUS; ALGORITHMS;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A fully distributed algorithm for estimating the center and coverage region of a wireless sensor network (WSN) is proposed. The proposed algorithm is useful in many applications, such as finding the required power for a certain level of connectivity in WSNs and localizing a service center in a network. The network coverage region is defined to be the smallest sphere that covers all the sensor nodes. The center and radius of the smallest covering sphere are estimated. The center estimation is formulated as a convex optimization problem using soft-max approximation. Then, diffusion adaptation is used for distributed optimization to estimate the center. After all the sensors obtain the center estimates, max consensus is used to calculate the radius distributively. The performance analysis of the proposed algorithm is provided, as a function of a design parameter controls the trade-off between the center estimation error and the convergence speed of the algorithm. Simulation results are provided.
引用
收藏
页码:1353 / 1357
页数:5
相关论文
共 17 条
  • [1] [Anonymous], 2014, CONVEX OPTIMIZATION
  • [2] Diffusion Adaptation Strategies for Distributed Optimization and Learning Over Networks
    Chen, Jianshu
    Sayed, Ali H.
    [J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2012, 60 (08) : 4289 - 4305
  • [3] Localized edge detection in sensor fields
    Chintalapudi, KK
    Govindan, R
    [J]. PROCEEDINGS OF THE FIRST IEEE INTERNATIONAL WORKSHOP ON SENSOR NETWORK PROTOCOLS AND APPLICATIONS, 2003, : 59 - 70
  • [4] Chrystal P., 1884, P EDINBURGH MATH SOC, V3, P30
  • [5] Fortune S., 1986, Proc. Second Ann. Symp. Comput. Geom. SCG New York, V86, P313
  • [6] Greene B., 2004, 22 TEX S REL ASTR, P0001
  • [7] PRIMITIVES FOR THE MANIPULATION OF GENERAL SUBDIVISIONS AND THE COMPUTATION OF VORONOI DIAGRAMS
    GUIBAS, L
    STOLFI, J
    [J]. ACM TRANSACTIONS ON GRAPHICS, 1985, 4 (02): : 74 - 123
  • [8] EFFICIENT ALGORITHMS FOR THE (WEIGHTED) MINIMUM CIRCLE PROBLEM
    HEARN, DW
    VIJAY, J
    [J]. OPERATIONS RESEARCH, 1982, 30 (04) : 777 - 795
  • [9] Analysis of Max-Consensus Algorithms in Wireless Channels
    Iutzeler, Franck
    Ciblat, Philippe
    Jakubowicz, Jeremie
    [J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2012, 60 (11) : 6103 - 6107
  • [10] Kundu S, 2012, IEEE GLOBE WORK, P431, DOI 10.1109/GLOCOMW.2012.6477611