Optimizing Weighted Graph Topology for Robust Network Information Dissemination

被引:0
|
作者
Liu, Zhenyi [1 ]
Zhang, Haopeng [1 ]
Smith, Philip [2 ]
Hui, Qing [1 ]
机构
[1] Texas Tech Univ, Dept Mech Engn, Lubbock, TX 79409 USA
[2] Texas Tech Univ, Ctr High Performance Comp, Lubbock, TX 79409 USA
关键词
LINEAR ITERATIONS; CONSENSUS;
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
The objective of this research is to develop a new hierarchical optimization-based design framework for balanced coordinated algorithms addressing robust sensor network information distribution problems so that the optimal responses to network damages and the optimal resource allocation will be achieved. In particular, this research will involve a two-stage hierarchical design in which the first stage is a network topology design for robustness and efficiency of connection in the network while the second stage is an optimal weight design for network graphs characterizing efficiency of information dissemination based on the graph topology obtained in the first stage. We convert the first stage design into a multi-objective optimization problem and the second stage design into a constrained optimization problem. To solve both proposed optimization problems, we develop a modified particle swarm optimization (MPSO) based stochastic algorithm to approximate optimal solutions of the multi-objective optimization problem and a semistable optimal control approach to solve the constrained optimization problem.
引用
收藏
页码:3329 / 3334
页数:6
相关论文
共 50 条
  • [1] A distributed and asynchronous approach for optimizing weighted graph matchings in wireless network services
    Ileri, Can Umut
    Dagdeviren, Orhan
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2019, 119 : 73 - 89
  • [2] A Modeling and Optimizing Method Based on the Topology Information of Wireless Sensor Network
    Li Shimin
    Wang Xingyu
    [J]. PROCEEDINGS OF THE 29TH CHINESE CONTROL CONFERENCE, 2010, : 4802 - 4806
  • [3] From Decoupling to Reconstruction: A Robust Graph Neural Network Against Topology Attacks
    Wei, Xiaodong
    Li, Yong
    Qin, Xiaowei
    Xu, Xiaodong
    Li, Ximin
    Liu, Mengjie
    [J]. 2020 12TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS AND SIGNAL PROCESSING (WCSP), 2020, : 263 - 268
  • [4] Neighborhood information dissemination in the star graph
    Fujita, S
    [J]. IEEE TRANSACTIONS ON COMPUTERS, 2000, 49 (12) : 1366 - 1370
  • [5] Introducing a graph topology for robust cooperation
    Locodi, A. M.
    O'Riordan, C.
    [J]. ROYAL SOCIETY OPEN SCIENCE, 2021, 8 (05):
  • [6] Feature Graph-Enabled Graphical Learning for Robust DSSE With Inaccurate Topology Information
    Hu, Jiaxiang
    Hu, Weihao
    Cao, Di
    Li, Sichen
    Chen, Jianjun
    Huang, Yuehui
    Chen, Zhe
    Blaabjerg, Frede
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2024, 39 (04) : 6091 - 6094
  • [7] Robust information dissemination in uncooperative environments
    Jun, S
    Ahamad, M
    Xu, JJ
    [J]. 25th IEEE International Conference on Distributed Computing Systems, Proceedings, 2005, : 293 - 302
  • [8] Robust State Estimation Method for Distribution Network Based on Graph Neural Network Incorporating Topology Knowledge
    Hu, Jiaxiang
    Cao, Di
    Hu, Weihao
    Chen, Jianjun
    Chen, Zhe
    [J]. Dianli Xitong Zidonghua/Automation of Electric Power Systems, 2023, 47 (10): : 84 - 97
  • [9] Robust Graph Signal Processing in the Presence of Uncertainties on Graph Topology
    Ceci, Elena
    Barbarossa, Sergio
    [J]. 2018 IEEE 19TH INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS (SPAWC), 2018, : 656 - 660
  • [10] ROBUST NETWORK TOPOLOGY INFERENCE
    Segarra, Santiago
    Marques, Antonio G.
    Mateos, Gonzalo
    Ribeiro, Alejandro
    [J]. 2017 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2017, : 6518 - 6522