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A novel cooperative caching algorithm for massive P2P caches

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Abstract

For an ISP (Internet Service Provider) that has deployed P2P caches in more than one ASs (autonomous systems), cooperative caching which makes their caches cooperate with each other can save more cost of carrying P2P traffic than independent caching. However, existing cooperative caching algorithms only use objects’ popularity as the measurement to decide which objects should be cached, and cost on intra-ISP links that has great impact on the benefits of cooperative caching is not considered. In this paper, we first model the cooperative caching problem as a NP-Complete problem, which is based on our analysis about the cost of serving requests with consideration of both the objects’ popularity and the cost on intra-ISP links. Then we propose a novel cooperative caching algorithm named cLGV (Cooperative, Lowest Global Value). The cLGV algorithm uses a new concept global value to estimate the benefits of caching or replacing an object in the cooperative caching system, and the global value of each object is evaluated according to not only objects’ popularity in each AS but also cost on intra-ISP links among ASs. Results of both synthetic and real traces driven simulations indicate that our cLGV algorithm can save the cost of carrying P2P traffic at least 23 % higher than that of existing cooperative caching algorithms.

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References

  1. Cisco Visual Networking Index (2012) 2011–2016.

  2. Wierzbicki A, Leibowitz N, Ripeanu M, Wozniak R (2004) “Cache replacement policies revisited: the case of P2P traffic”, in Proc. GP2P 2004., pp 182–189

    Google Scholar 

  3. Hefeeda M, Saleh O (2008) Traffic modeling and proportional partial caching for peer-to-peer systems. IEEE Transactions on Networking 16(6):1447–1460

    Article  Google Scholar 

  4. Packeteer (2012) http://www.packeteer.com/

  5. Xie H, Yang YR, Krishnamurthy A, Silberschatz A (2008) P4P: provider portal for applications. SIGCOMM

  6. PeerCache (2012) http://www.joltid.com/

  7. CacheLogic (2012) http://www.velocix.com/

  8. PPCache (2012) http://www.net-east.com/

  9. Hefeeda M, Noorizadeh B (2010) On the benefits of cooperative proxy caching for peer-to-peer traffic. IEEE Transactions on Paralletl and Distributed Systems 21(7):998–1010

    Article  Google Scholar 

  10. Dimokas N, Katsaros D, Manolopoulos Y (2008) Cooperative caching in wireless multimedia sensor networks. Mobile Networks and Applications 13(3–4):337–356

    Google Scholar 

  11. Wei Q, Veeravalli B, Zeng L (2008) “DWC2: A dynamic weight-based cooperative caching scheme for object-based storage cluster”, in Proceedings of 2008 IEEE International Conference on Cluster Computing

  12. Karp RM (1972) “Reducibility among combinatorial problems”, in complexity of computer computations. Plenum, New York, pp 85–103

    Book  Google Scholar 

  13. OMNeT++, URL: http://www.omnetpp.org/

  14. Zhar H, Wong AK, Jiang H, Sun Y, Li J (2011) “Optimal P2P cache sizing: a monetary cost perspective on capacity design of caches to reduce P2P traffic”, in proc. ICPADS 2011., pp 565–572

    Google Scholar 

  15. MultiProbe Project (2012) http://multiprobe.ewi.tudelft.nl

  16. MaxMind GeoIP Database, URL: http://www.maxmind.com

Download references

Acknowledgements

This work is supported in part by National Science and Technology Major Projects of the Ministry of Industry and Information Technology of China (Grant No. 2010ZX03004-001 and 2011ZX03005-004-02) and National Science Foundation of China (Grant No. 61102076). We are also grateful to Multiprobe team for making the DBD2 data set for simulation purposes.

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Authors and Affiliations

  1. High Performance Network Lab, Chinese Academy of Sciences, Beijing, China

    Yan Zhang, Xu Zhou, Yinlong Liu, Bo Wang & Song Ci

Authors
  1. Yan Zhang
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  2. Xu Zhou
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  3. Yinlong Liu
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  4. Bo Wang
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  5. Song Ci
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Correspondence to Xu Zhou.

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Zhang, Y., Zhou, X., Liu, Y. et al. A novel cooperative caching algorithm for massive P2P caches. Peer-to-Peer Netw. Appl. 6, 425–433 (2013). https://doi.org/10.1007/s12083-013-0211-9

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  • DOI: https://doi.org/10.1007/s12083-013-0211-9

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