Peer-to-Peer Networking and Applications

, Volume 7, Issue 4, pp 427–443 | Cite as

P2P storage systems: Study of different placement policies

  • Stéphane Caron
  • Frédéric Giroire
  • Dorian Mazauric
  • Julian Monteiro
  • Stéphane Pérennes


In a P2P storage system using erasure codes, a data block is encoded in many redundancy fragments. These fragments are then sent to distinct peers of the network. In this work, we study the impact of different placement policies of these fragments on the performance of storage systems. Several practical factors (easier control, software reuse, latency) tend to favor data placement strategies that preserve some degree of locality. We compare three policies: two of them are local, in which the data are stored in logical neighbors, and the other one, global, in which the data are spread randomly in the whole system. We focus on the study of the probability to lose a data block and the bandwidth consumption to maintain such redundancy. We use simulations to show that, without resource constraints, the average values are the same no matter which placement policy is used. However, the variations in the use of bandwidth are much more bursty under the local policies. When the bandwidth is limited, these bursty variations induce longer maintenance time and henceforth a higher risk of data loss. We then show that a suitable degree of locality could be introduced in order to combine the efficiency of the global policy with the practical advantages of a local placement. Additionally, we propose a new external reconstruction strategy that greatly improves the performance of local placement strategies. Finally, we give analytical methods to estimate the mean time to the occurrence of data loss for the three policies.


Distributed storage P2P system Data placement Data life time Mean time to data loss Performance evaluation Markov chains 


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Stéphane Caron
    • 1
  • Frédéric Giroire
    • 2
  • Dorian Mazauric
    • 3
  • Julian Monteiro
    • 4
  • Stéphane Pérennes
    • 2
  1. 1.Technicolor Palo Alto Research CenterPalo AltoUSA
  2. 2.MASCOTTE, INRIA, I3S, CNRS, UNSSophia AntipolisFrance
  3. 3.Department of Computer ScienceColumbia UniversityNew YorkUSA
  4. 4.Instituto de Matemática e Estatística - IME-USPSao PauloBrazil

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