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Poster: An Adaptive Copy Spraying Scheme for Data Forwarding in Mobile Opportunistic Networks

Published:22 June 2015Publication History

ABSTRACT

Mobile opportunistic network (MON) is a new paradigm which exploits node contacts to forward data, enabling numerous and impressive applications. The data copy spraying scheme is a challenging problem in MON, due to the mobility of nodes and lack of global knowledge, it hence captures great interests from research communities. Traditional algorithms allocate data copies with node's statistical information and neglect the temporal contact feature, resulting in a poor delivery performance. We propose AS, an adaptive data copy spraying scheme in MON. AS adjusts the number of copies dynamically based on the temporal contact feature among nodes. Theoretical analysis verifies that AS achieves a lower mean delivery delay than SprayWait, one of the state-of-the-art works. Simulation results show that AS improves the packet delivery ratio simultaneously.

References

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  1. Poster: An Adaptive Copy Spraying Scheme for Data Forwarding in Mobile Opportunistic Networks

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    • Published in

      cover image ACM Conferences
      MobiHoc '15: Proceedings of the 16th ACM International Symposium on Mobile Ad Hoc Networking and Computing
      June 2015
      436 pages
      ISBN:9781450334891
      DOI:10.1145/2746285

      Copyright © 2015 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 22 June 2015

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      Acceptance Rates

      MobiHoc '15 Paper Acceptance Rate37of250submissions,15%Overall Acceptance Rate296of1,843submissions,16%

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