User-experience-based availability analysis model and its application in P2P storage systems

  • Yu WuEmail author
  • Zhi Yang
  • Zhi Qu
  • Zhen Xiao
  • YaFei Dai
Research Papers


Data availability is one of the most important properties of peer-to-peer (P2P) storage systems. Availability analysis model and data placement are two key design choices. Users in P2P storage system are both providers and customers. This characteristic determines that the availability analysis must be user-centric, and thereby enhance the quality of service and decrease the system cost. The popular approach in recent studies is simple random placement with steady-state model, which has the following drawbacks: 1) It ignores the up/down patterns of nodes, whose availability is over-estimated or under-estimated at different periods of time. 2) It ignores the access patterns of users, so the availability perceived by users is hard to evaluate precisely. 3) It ignores the huge difference of nodes’ availability, thus leading to the absence of incentive. This paper proposes a novel user-experience-based availability model, which evaluates the availability of P2P storage system in terms of user experience, which can degenerate to traditional availability analysis model. Based on the new model, this paper proposes decentralized data placement algorithms for two typical P2P storage applications: “data sharing” and “personal backup”. By the trace-driven simulation, we prove that our methods can enhance the availability perceived by users greatly, reduce the variance of the availability dramatically and eliminate the nodes with low availability in data-sharing applications; meanwhile, it can provide different-level service to encourage users according to their contributions.


P2P storage user experience availability data replacement 


  1. 1.
    Bhagwan R, Tati K, Cheng Y, et al. Total recall: system support for automated availability management. In: Proceedings of the 1st ACM/Usenix Symposium on Networked Systems Design and Implementation, San Francisco, USA, 2004. 337–350Google Scholar
  2. 2.
    Bhagwan R, Savage S, Voelker G. Replication strategies for highly available peer-to-peer storage systems. In: Proceedings of FuDiCo: Future Directions in Distributed Computing, Bertinoro, Italy, 2002Google Scholar
  3. 3.
    Weatherspoon H, Kubiatowicz J. Erasure coding vs. replication: a quantitative comparison. In: Proceedings of IPTPS, Cambridge, USA, 2002Google Scholar
  4. 4.
    Blake C, Rodrigues R. High availability, scalable storage, dynamic peer networks: pick two. In: Proceedings of the 9th Workshop on Hot Topics in Operating Systems, Lihue, Hawaii, USA, 2003Google Scholar
  5. 5.
    Chun B G, Dabek F, Haeberlen A, et al. Efficient replica maintenance for distributed storage systems. In: Proceedings of the 3rd USENIX Symposium on Networked Systems Design and Implementation, San Jose, USA, 2006Google Scholar
  6. 6.
    Adya A, Bolosky W J, Castro M, et al. FARSITE: federated, available, and reliable storage for an incompletely trusted environment. In: Proceedings of OSDI, Boston, USA, 2002Google Scholar
  7. 7.
    Kubiatowicz J, Bindel D, Chen Y, et al. OceanStore: an architecture for global-scale persistent storage. In: Proceedings of ASPLOS, Cambridge, USA, 2000Google Scholar
  8. 8.
    Ramanathan M. Increasing object availability in peer-to-peer systems. In: Proceedings of the 18th International Parallel and Distributed Processing Symposium, Santa Fe, New Mexico, 2004Google Scholar
  9. 9.
    Lin W K, Ye C, Chiu D M. Decentralized replication algorithms for improving file availability in P2P networks. In: Quality of Service, 15th IEEE International Workshop, Evanston, USA, 2007. 29–37Google Scholar
  10. 10.
    Kim K. Time-related replication for P2P storage system. In: Proceedings of the 7th International Conference on Networking, Cancun, Mexico, 2008Google Scholar
  11. 11.
    Tian J, Yang Z, Dai Y F. A data placement scheme with time-related model for P2P storages. In: Proceedings of the 7th IEEE International Conference on Peer-to-Peer Computing, Galway, Ireland, 2007Google Scholar
  12. 12.
    Liu H Y. Feature analysis of the resources and use behaviors in P2P file-sharing system Maze. Dissertation for Master’s Degree. Beijing: Peking University, 2005Google Scholar
  13. 13.
    Gao Q, Yang Z, Tian J, et al. A hierarchically differential P2P storage architecture. J Software, 2007, 18: 2481–2494CrossRefGoogle Scholar
  14. 14.
    Tian J, Dai Y. Understanding the dynamic of Peer-to-Peer systems. In: Proceedings of the 6th International Workshop on Peer-to-Peer Systems, Bellevue, USA, 2007Google Scholar
  15. 15.
    Yang M, Zhang Z, Li X, et al. An empirical study of free-riding behavior in the Maze P2P file-sharing system. In: Proceedings of IPTPS, Ithaca, USA, 2005Google Scholar
  16. 16.
    Lian Q, Peng Y, Yang M, et al. Robust incentives via multi-level Tit-for-Tat. Int J Concurr Comp, 2008, 20: 167–178Google Scholar

Copyright information

© Science China Press and Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.Department of Computer SciencePeking UniversityBeijingChina

Personalised recommendations