Modeling Restrained Epidemic Routing on Complex Networks

被引:3
|
作者
Kawabata, Natsuko [1 ]
Yamasaki, Yasuhiro [1 ]
Ohsaki, Hiroyuki [1 ]
机构
[1] Kwansei Gakuin Univ, Grad Sch Sci & Technol, Sanda, Hyogo 6691337, Japan
来源
2019 IEEE 43RD ANNUAL COMPUTER SOFTWARE AND APPLICATIONS CONFERENCE (COMPSAC), VOL 1 | 2019年
关键词
epidemic routing; restrained epidemic routing; degree-based mean field approximation; SIR (Susceptible-Infected-Recovered) model; MOBILITY; IMPACT;
D O I
10.1109/COMPSAC.2019.00049
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
To realize an efficient DTN (Delay/Disruption-Tolerant Networking) routing, it is required to quickly deliver the message from the source node to the destination node as well as to quickly delete disused message replicas from the network. Epidemic routing, which indefinitely forwards message replicas to all encountered nodes, realizes the near-optimal message delivery delay when a limited number of messages are transferred. However, its performance is significantly degraded when a number of messages are transferred simultaneously. In our previous work, we have proposed a simple but effective extension to epidemic routing called restrained epidemic routing, which intentionally suppresses message forwardings at the later stage of epidemic-style message dissemination. In this paper, we analyze the characteristics of restrained epidemic routing when the contact relation between nodes is given by a general contact model such as complex networks. Specifically, we describe the dynamics of restrained epidemic routing on a complex network with a given degree distribution as differential equations using the degree-based mean field approximation.
引用
收藏
页码:285 / 290
页数:6
相关论文
共 50 条
  • [1] Performance modeling of epidemic routing
    Zhang, Xiaolan
    Neglia, Giovanni
    Kurose, Jim
    Towsley, Don
    NETWORKING 2006: NETWORKING TECHNOLOGIES, SERVICES, AND PROTOCOLS; PERFORMANCE OF COMPUTER AND COMMUNICATION NETWORKS; MOBILE AND WIRELESS COMMUNICATIONS SYSTEMS, 2006, 3976 : 827 - 839
  • [2] Performance modeling of epidemic routing
    Zhang, Xiaolan
    Neglia, Giovanni
    Kurose, Jim
    Towsley, Don
    COMPUTER NETWORKS, 2007, 51 (10) : 2867 - 2891
  • [3] On Modeling The Impact of Selfish Behaviors on Limited Epidemic Routing in Delay Tolerant Networks
    Wu, Yahui
    Deng, Su
    Huang, Hongbin
    WIRELESS PERSONAL COMMUNICATIONS, 2013, 71 (04) : 2759 - 2782
  • [4] On Modeling The Impact of Selfish Behaviors on Limited Epidemic Routing in Delay Tolerant Networks
    Yahui Wu
    Su Deng
    Hongbin Huang
    Wireless Personal Communications, 2013, 71 : 2759 - 2782
  • [5] Modeling the effects of social impact on epidemic spreading in complex networks
    Ni, Shunjiang
    Weng, Wenguo
    Zhang, Hui
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2011, 390 (23-24) : 4528 - 4534
  • [6] Prioritized Epidemic Routing for Opportunistic Networks
    Ramanathan, Ram
    Hansen, Richard
    Basu, Prithwish
    Rosales-Hain, Regina
    Krishnan, Rajesh
    MOBIOPP'07 - PROCEEDINGS OF THE FIRST INTERNATIONAL MOBISYS WORKSHOP ON MOBILE OPPORTUNISTIC NETWORKING, 2007, : 62 - 66
  • [7] The Capacity of Epidemic Routing in Vehicular Networks
    Yoo, Joon
    Choi, Sunwoong
    Kim, Chong-kwon
    IEEE COMMUNICATIONS LETTERS, 2009, 13 (06) : 459 - 461
  • [8] Modeling strategies for effectively routing freight trains through complex networks
    Murali, Pavankumar
    Ordonez, Fernando
    Dessouky, Maged M.
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2016, 70 : 197 - 213
  • [9] EPIDEMIC ROUTING WITH IMMUNITY IN DELAY TOLERANT NETWORKS
    Mundur, Padma
    Seligman, Matthew
    Lee, Ginnah
    2008 IEEE MILITARY COMMUNICATIONS CONFERENCE: MILCOM 2008, VOLS 1-7, 2008, : 1997 - +
  • [10] Congestion Control for Epidemic Routing in Opportunistic Networks
    Bialon, Raphael
    Graffi, Kalman
    2019 INTERNATIONAL CONFERENCE ON INTERNET OF THINGS (ITHINGS) AND IEEE GREEN COMPUTING AND COMMUNICATIONS (GREENCOM) AND IEEE CYBER, PHYSICAL AND SOCIAL COMPUTING (CPSCOM) AND IEEE SMART DATA (SMARTDATA), 2019, : 102 - 109