Exploiting Overlay Networks Features To Enhance The Performance Of The File Mover

  • C. Anglano
  • M. Canonico
Conference paper
Part of the Signals and Communication Technology book series (SCT)

Abstract

The File Mover is a file transfer infrastructure, based on the overlay networks paradigm, specifically conceived to provide high-performance file transfers for Data Grids. In its current implementation, the File Mover exploits only in part the potential benefits typical of overlay networks. In this chapter we consider three possible extensions of the File Mover, aimed at increasing its performance, that better exploit the characteristics of overlay networks. The performance improvements obtained with these extensions are demonstrated by means of a set of experiments, in which the performance obtained by an extended version of the File Mover has been compared with that attained by its standard version.

Keywords

Data Grid Overlay Network Distribute Hash Table Virtual Link Network Path 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    D.G. Andersen, H. Balakrishnan, M.F. Kaashoek, and R.Morris. “Resilient overlay networks”. In Proc. of 18th ACM Symp. on Operating Systems Principles, Banff, Canada, Oct. 2001.Google Scholar
  2. [2]
    D.G. Andersen, A.C. Snoeren, and H. Balakrishnan. “Best-path vs. multi-path overlay routing”. In IMC ’03: Proc. of the 3rd ACM SIGCOMM conference on Internet measurement, pages 91–100. ACM Press, New York, NY, USA, 2003.Google Scholar
  3. [3]
    C. Anglano and M. Canonico. “The file mover: High-performance file transfer for the grid”. Concurrency and Computation: Practice and Experience, 2007. Submitted for publication. Available from http://dcs.di.unipmn.it/.Google Scholar
  4. [4]
    M. Cai, A. Chervenak, and M. Frank. {“A peer-to-peer replica location service based on a distributed hash table”}. In Proc. of Supercomputing 2004, Pittsburgh, PA, USA. IEEE Press, 2004.Google Scholar
  5. [5]
    A. Chervenak, I. Foster, C. Kesselman, C. Salisbury, and S. Tuecke. {“The data grid: Towards an architecture for the distributed management and analysis of large scientific datasets”}. Journal of Network and Computer Applications, 23:187–200, 2001.CrossRefGoogle Scholar
  6. [6]
    A.L.H. Chow, L. Golubchik, J.C.S. Lui, and W.-J. Lee. “Multi-path streaming: optimization of load distribution”. Performance Evaluation, 62(1-4):417–438, 2005.CrossRefGoogle Scholar
  7. [7]
    M. Dahlin, B. Baddepudi V. Chandra, L. Gao, and A. Nayate. “End-to-end wan service availability”. IEEE/ACM Transactions on Networking, 11(2):300–313, 2003.CrossRefGoogle Scholar
  8. [8]
    D.D. Doval and D. O’Mahony. “Overlay networks: A scalable alternative for p2p”. IEEE Internet Computing, pages 79–82, July–August 2003.CrossRefGoogle Scholar
  9. [9]
    L. Golubchik and J.C.S. Lui. “Multi-path streaming: is it worth the trouble?”. ACM SIGMETRICS Performance Evaluation Review, 30(3):12–14, 2002.CrossRefGoogle Scholar
  10. [10]
    L. Golubchik, J.C.S. Lui, T.F. Tung, A.L.H. Chow, W.-J. Lee, G. Franceschinis, and C. Anglano. “Multi-path continuous media streaming: What are the benefits?”. Performance Evaluation, 49(1-4):429–449, 2002.CrossRefGoogle Scholar
  11. [11]
    Y. Gu and R.L. Grossman. “Optimizing udp-based protocol implementation”. In Proc. of the Third International Workshop on Protocols for Fast Long-Distance Networks PFLDnet, 2005.Google Scholar
  12. [12]
    Iperf: The TCP/UDP Bandwidth Measurement Tool. http://dast.nlanr.net/Projects/Iperf, 2007.Google Scholar
  13. [13]
    C. Labovitz, A. Ahuja, A. Bose, and F. Jahanian. “Delayed internet routing convergence”. InProc. of ACM SIGCOMM, pages 175–187, Stockolm, Sweden, September 2000.CrossRefGoogle Scholar
  14. [14]
    Linux Advanced Routing & Traffic Control. http://lartc.org/, 2007.Google Scholar
  15. [15]
    S.-J. Lee, P. Sharma, S. Banerjee, S. Basu, and R. Fonseca. “Measuring bandwidth between planetlab nodes”. In Proc. of the Passive and Active Measurement Workshop (PAM 2005), pages 292–305, Springer, Berlin, 2005.Google Scholar
  16. [16]
    Z. Ling and I. Lee. “Adaptive multi-path video streaming”. In ISM ’06: Proc. of the Eighth IEEE International Symposium on Multimedia, pages 399–406. IEEE Computer Society, Washington, DC, USA, 2006.CrossRefGoogle Scholar
  17. [17]
    H.B. Newman, M.H. Ellisman, and J.H. Orcutt. “Data-intensive e-Science frontier research”. Communications of the ACM, 46(11), Nov. 2003.CrossRefGoogle Scholar
  18. [18]
    V. Paxson. {“End-to-end routing behavior in the Internet”. In Proc. of ACM SIGCOMM, pages 25–38, Stanford, CA, August 1996.Google Scholar
  19. [19]
    V. Paxson. {“End-to-end internet packet dynamics”. In Proc. ACM SIGCOMM, pages 139–152, Cannes, France, September 1997.Google Scholar
  20. [20]
    A. Pescape, S. Avallone, and G. Ventre. “Analysis and experimentation of internet traffic generator”. In Proc. of the New2an, pages 70–75, 2004.Google Scholar
  21. [21]
    R.S. Prasad, M. Murray, C. Dovrolis, and K. Claffy,{“Bandwidth estimation: metrics, measurements techniques, and tools}.{In IEEE Network, Dec. 2003}Google Scholar
  22. [22]
    K. Ranganathan and I. Foster. {“Simulation studies of computation and data scheduling algorithms for data grids”}. Journal of Grid Computing, 1(1):53–62, 2003.CrossRefGoogle Scholar
  23. [23]
    S. Savage, A. Collins, E. Hoffman, J. Snell, and T. Andersonr. “The end-to-end effects of internet path selection”. In SIGCOMM ’99: Proc. of the conference on Applications, technologies, architectures, and protocols for computer communicationr, pages 289–299. ACM Press, New York, NY, USA, 1999.Google Scholar
  24. [24]
    H. Tangmunarunkit, R. Govindan, S. Shenker, and D. Estrin. {“The impact of routing policy on Internet paths”. In Proc. IEEE Infocom ’01, Anchorage, Alaska, Anchorage, AK, USA, April 2001.Google Scholar
  25. [25]
    The nistnet project. http://snad.ncsl.nist.gov/nistnet/, 2007.
  26. [26]
    The plab project. http://www.grid.unina.it/software/Plab, 2007.
  27. [27]
    The planetlab project. http://www.planet-lab.org, 2007.
  28. [28]
    S. Venugopal, R. Buyya, and K. Ramamohanarao. {“A taxonomy of data grids for distributed data sharing, management, and processing”}. ACM Computing Surveys, 38(1), June 2006.Google Scholar
  29. [29]
    B. White, J. Lepreau, L. Stoller, R. Ricci, S. Guruprasad, M. Newbold, M. Hibler, C. Barb, and A. Joglekar. “An integrated experimental environment for distributed systems and networks”. ACM/SIGOPS/Operating Systems Review, 36(SI):255–270, 2002.CrossRefGoogle Scholar
  30. [30]
    R. Wolski. “Dynamically forecasting network performance using the network weather service”. Cluster Computing, 1(1):119–132, Jan. 1998.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • C. Anglano
    • 1
  • M. Canonico
    • 1
  1. 1.Dipartimento di InformaticaUniversità del Piemonte OrientaleAlessandriaItaly

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