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Feature-based content dissemination process in opportunistic networks

Zehni, M ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/PIMRC.2015.7343529
  3. Abstract:
  4. In order to respond to drastically increased traffic demands in mobile networks such as cellulars, opportunistic communication has been introduced as a data offloading strategy. Delivering the contents using peer-to-peer data dissemination is more preferable compared to epidemic diffusion schemes. To implement peer-to-peer dissemination, one needs to define the peer selection and content dissemination policies. Efficient content dissemination relies on the selection of suitable peers. Besides that, the peers require to choose what contents to be transmitted between them. In this paper, we propose multi-level master/slave peer selection algorithm (MMSA) and variance-based multi-metric chunk selection algorithm (VMMA) which ensure efficient content dissemination with reduced signaling overhead. VMMA can use the local and global features of the contents to prioritize the contents. A mathematical analysis that considers the time varying nature of the network and traces the evolution of distribution process is provided. The simulation results demonstrate the advantages provided by these algorithms. The simulation results match the mathematical analysis
  5. Keywords:
  6. content dissemination ; fragment selection ; Opportunistic peer-to-peer communications ; Radio communication ; Time varying networks ; Wireless networks ; Distribution process ; Fragment selections ; Mathematical analysis ; Opportunistic communications ; Opportunistic networks ; Peer selection ; Peer-to-peer communications ; Distributed computer systems
  7. Source: 26th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2015, 30 August 2015 through 2 September 2015 ; Volume 2015-December , 2015 , Pages 1464-1469 ; 9781467367820 (ISBN)
  8. URL: http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=7343529&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D7343529