• DocumentCode
    643944
  • Title

    Predicting Availability of Mobile Peers in Large Peer-to-Peer Networks

  • Author

    Sipos, Marton Akos ; Ekler, Peter

  • Author_Institution
    Dept. of Autom. & Appl. Inf., Budapest Univ. of Technol. & Econ., Budapest, Hungary
  • fYear
    2013
  • fDate
    29-30 Aug. 2013
  • Firstpage
    71
  • Lastpage
    77
  • Abstract
    Peer-to-peer (P2P) applications for mobile devices are becoming more and more popular because of increasing bandwidth, computational performance and storage capabilities. Such a mobile based distributed architecture offers significant advantages in several scenarios from the perspective of both users and network operators. In these situations, a certain redundancy must be built into the system because the availability of the nodes can vary greatly. The goal of this paper is to present a methodology to minimize the necessary redundancy by predicting the number of available nodes. The prediction is performed in two steps, first an estimation is done locally at the node level, then a centralized aggregation is executed. We propose a hypothesis which highlights the key advantages of our solution when compared to single step estimation. Finally we discuss about the correctness of the computed redundancy.
  • Keywords
    computer network reliability; mobile computing; mobile handsets; peer-to-peer computing; P2P network; centralized aggregation; distributed architecture; mobile device; mobile peer availability; peer-to-peer network; single step estimation; storage capability; Accuracy; Availability; Batteries; Computational modeling; Peer-to-peer computing; Predictive models; Redundancy; Availability prediction; Distributed storage; Mobile devices; Peer-to-peer networks; Redundancy optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering of Computer Based Systems (ECBS-EERC), 2013 3rd Eastern European Regional Conference on the
  • Conference_Location
    Budapest
  • Type

    conf

  • DOI
    10.1109/ECBS-EERC.2013.18
  • Filename
    6664512