Cache-Enabled Super-Peer Overlays for Multiple Job Submission on Grids

  • Pasquale Cozza
  • Domenico Talia
  • Carlo Mastroianni
  • Ian Kelley
  • Ian Taylor

Many types of distributed scientific and commercial applications require the submission of a large number of independent jobs. One highly successful and low cost mechanism for acquiring the necessary compute power is the "publicresource computing" paradigm, which exploits the computational power of private computers. Recently decentralized peer-to-peer and super-peer technologies have been proposed for adaptation in these systems. A super-peer protocol, proposed earlier by this group, is used for the execution of jobs based upon the volunteer requests of workers, and a super-peer overlay is used to perform two kinds of matching operations: the assignment of jobs to workers and providing workers the input data needed for job execution. This paper extends this superpeer protocol to account for a more dynamic and general scenario, in which: (i) workers can leave the network at any time; (ii) each job is executed multiple times, either to obtain better statistical accuracy or to perform parameter sweep analysis; and, (iii) input data is replicated and distributed to multiple data caches on-the-fly, in an effort to improve performance in terms of data availability, fault tolerance and execution time. A simulation study was performed to analyze the latest iteration of the super-peer protocol and specifically evaluate the new features.


Grid data caching job execution public resource computing super-peer 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    David P. Anderson. Public computing: Reconnecting people to science. In Proceedings of Conference on Shared Knowledge and the Web, pages 17-19, November 2003.Google Scholar
  2. [2]
    David P. Anderson. Boinc: A system for public-resource computing and storage. In GRID ’04: Proceedings of the Fifth IEEE/ACM International Workshop on Grid Computing (GRID’04), pages 4-10, Washington, DC, USA, 2004. IEEE Computer Society.Google Scholar
  3. [3]
    David P. Anderson, Jeff Cobb, Eric Korpela, Matt Lebofsky, and Dan Werthimer. Seti@home: an experiment in public-resource computing. Communications of the ACM, 45 (11), 2002.Google Scholar
  4. [4]
    Climate@HOME Web site.
  5. [5]
    B. Cohen. Incentives build robustness in bittorrent. In Proceedings of the First Workshop on Economics of Peer-to-Peer Systems, June 2003.Google Scholar
  6. [6]
    Pasquale Cozza, Carlo Mastroianni, Domenico Talia, and Ian Taylor. A super-peer protocol for multiple job submission on a grid. In Euro-Par 2006 Workshops, volume 4375 of LNCS, pages 116-125, Dresden, Germany, 2007. Springer-Verlag.Google Scholar
  7. [7]
    Einstein@HOME Web site.
  8. [8]
    GridOneD Web site.
  9. [9]
    KaZaA Web site.
  10. [10]
    Carlo Mastroianni, Domenico Talia, and Oreste Verta. A super-peer model for resource discovery services in large-scale grids. Future Generation Computer Systems, 21(8):1235-1248, 2005.CrossRefGoogle Scholar
  11. [11]
    Napster website.
  12. [12]
    Domenico Talia and Paolo Trunfio. Toward a synergy between p2p and grids. IEEE Internet Computing, 7(4):96-95, 2003.CrossRefGoogle Scholar
  13. [13]
    Beverly Yang and Hector Garcia-Molina. Designing a super-peer network. In 19th International Conference on Data Engineering ICDE, 2003.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Pasquale Cozza
    • 1
  • Domenico Talia
    • 1
  • Carlo Mastroianni
    • 2
  • Ian Kelley
    • 3
  • Ian Taylor
    • 3
  1. 1.Dip. Elettronica Informatica e SistemisticaUniversitá della CalabriaItaly
  2. 2.ICAR-CNRItaly
  3. 3.School of Computer ScienceCardiff UniversityUK

Personalised recommendations