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Community-Based Message Opportunistic Transmission

In: Transforming Healthcare Through Information Systems

Author

Listed:
  • Sheng Zhang

    (Nanchang Hangkong University)

  • Pengliu Tan

    (Nanchang Hangkong University)

  • Xiaoling Bao

    (Nanchang Hangkong University)

  • William Wei Song

    (Dalarna University)

  • Xiaodong Liu

    (Nanchang Hangkong University)

Abstract

A Mobile Social Networks (MSN) is a kind of opportunistic network, which is composed of numerous mobile nodes with social characteristic. By now, the prevalent community-based routing algorithms mainly choose the optimal social characteristic node to forward messages, however they rarely consider the effects of community distribution on mobile nodes and time-varying characteristics of network. These algorithms usually lead to a high consumption of network resources and a low successful delivery ratio if they are used directly in mobile social networks. In order to solve this problem, we build a time-varying community-based network model, and propose a community-aware message opportunistic transmission algorithm (CMOT) in this paper. For inter-community messages transmission, the CMOT chooses an optimal community path by comparing the community transmission probability. In local communities, messages are forwarded according to the encounter probability between nodes. The simulation results show that, in comparison with classical routing algorithms, such as PRoPHET, MaxProp, Spray and Wait, and CMTS, the CMOT can improve the successful delivery ratio of messages and reduce network overhead obviously.

Suggested Citation

  • Sheng Zhang & Pengliu Tan & Xiaoling Bao & William Wei Song & Xiaodong Liu, 2016. "Community-Based Message Opportunistic Transmission," Lecture Notes in Information Systems and Organization, in: Doug Vogel & Xitong Guo & Henry Linger & Chris Barry & Michael Lang & Christoph Schneider (ed.), Transforming Healthcare Through Information Systems, edition 1, pages 79-93, Springer.
    • Handle: RePEc:spr:lnichp:978-3-319-30133-4_6
    DOI: 10.1007/978-3-319-30133-4_6
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