Time-Varying Graphs and Dynamic Networks

被引:0
|
作者
Casteigts, Arnaud [1 ]
Flocchini, Paola [1 ]
Quattrociocchi, Walter [2 ]
Santoro, Nicola [3 ]
机构
[1] Univ Ottawa, Ottawa, ON K1N 6N5, Canada
[2] Univ Siena, Siena, Italy
[3] Carleton Univ, Ottawa, ON, Canada
来源
关键词
Highly dynamic networks; delay-tolerant networks; challenged networks; time-varying graphs; evolving graphs; dynamic graphs; MOBILE;
D O I
10.1080/17445760.2012.668546
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The past decade has seen intensive research efforts on highly dynamic wireless and mobile networks (variously called delay-tolerant, disruptive-tolerant, challenged, opportunistic, etc) whose essential feature is a possible absence of end-to-end communication routes at any instant. As part of these efforts, a number of important concepts have been identified, based on new meanings of distance and connectivity. The main contribution of this paper is to review and integrate the collection of these concepts, formalisms, and related results found in the literature into a unified coherent framework, called TVG (for time-varying graphs). Besides this definitional work, we connect the various assumptions through a hierarchy of classes of TVGs defined with respect to properties with algorithmic significance in distributed computing. One of these classes coincides with the family of dynamic graphs over which population protocols are defined. We examine the (strict) inclusion hierarchy among the classes. The paper also provides a quick review of recent stochastic models for dynamic networks that aim to enable analytical investigation of the dynamics.
引用
收藏
页码:346 / 359
页数:14
相关论文
共 50 条
  • [41] Dynamic behavior of nonautonomous cellular neural networks with time-varying delays
    Long, Shujun
    Li, Hongheng
    Zhang, Yongxin
    [J]. NEUROCOMPUTING, 2015, 168 : 846 - 852
  • [42] On the convergence of time-varying fusion algorithms: Application to localization in dynamic networks
    Safavi, Sam
    Khan, Usman A.
    [J]. 2016 IEEE 55TH CONFERENCE ON DECISION AND CONTROL (CDC), 2016, : 4907 - 4912
  • [43] Stochastic Graph Filtering on Time-Varying Graphs
    Isufi, Elvin
    Simonetto, Andrea
    Loukas, Andreas
    Leus, Geert
    [J]. 2015 IEEE 6TH INTERNATIONAL WORKSHOP ON COMPUTATIONAL ADVANCES IN MULTI-SENSOR ADAPTIVE PROCESSING (CAMSAP), 2015, : 89 - 92
  • [44] Visual exploration of complex time-varying graphs
    Kumar, Gautam
    Garland, Michael
    [J]. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2006, 12 (05) : 805 - 812
  • [45] Interpreting Time-Varying Dynamic Bayesian Networks for Earth Climate Modelling
    Valero-Leal, Enrique
    Larranaga, Pedro
    Bielza, Concha
    [J]. INTERNATIONAL CONFERENCE ON PROBABILISTIC GRAPHICAL MODELS, VOL 186, 2022, 186
  • [46] Game of the Byzantine Generals on Time-Varying Graphs
    Li, Yuke
    Yu, Changbin
    [J]. IFAC PAPERSONLINE, 2020, 53 (02): : 16958 - 16963
  • [47] Time-varying Contact Management with Dynamic Programming for LEO Satellite Networks
    Wang, Feng
    Jiang, Dingde
    Chen, Yingjie
    Song, Houbing
    Lv, Zhihan
    [J]. 2021 17TH INTERNATIONAL CONFERENCE ON MOBILITY, SENSING AND NETWORKING (MSN 2021), 2021, : 479 - 485
  • [48] Online graph learning for time-varying graphs
    Si, Binqiang
    Luo, Dongqi
    Zhu, Jihong
    [J]. ELECTRONICS LETTERS, 2022, 58 (16) : 623 - 626
  • [49] Finite-time synchronization of uncertain complex dynamic networks with time-varying delay
    Yiping Luo
    Yuejie Yao
    [J]. Advances in Difference Equations, 2020
  • [50] Finite-time synchronization of uncertain complex dynamic networks with time-varying delay
    Luo, Yiping
    Yao, Yuejie
    [J]. ADVANCES IN DIFFERENCE EQUATIONS, 2020, 2020 (01)