Are P2P Data-Dissemination Techniques Viable in Today’s Data-Intensive Scientific Collaborations?

  • Samer Al-Kiswany
  • Matei Ripeanu
  • Adriana Iamnitchi
  • Sudharshan Vazhkudai
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4641)


The interest among a geographically distributed user base to mine massive collections of scientific data propels the need for efficient data dissemination solutions. An optimal data distribution scheme will find the delicate and often application-specific balance among conflicting success metrics such as minimizing transfer times, minimizing the impact on the network, and uniformly distributing load among participants. We use simulations to explore the performance of classes of data-distribution techniques, some of which successfully deployed in large peer-to-peer communities, in the context of today’s data-centric scientific collaborations. Based on these simulations we derive several recommendations for data distribution in real-world science collaborations.


  1. 1.
    Iamnitchi, A., Ripeanu, M., Foster, I.: Small-World File-Sharing Communities. In: Infocom2004, Hong Kong (2004)Google Scholar
  2. 2.
    Iamnitchi, A., Doraimani, S., Garzoglio, G.: Filecules in High-Energy Physics: Characteristics and Impact on Resource Management. In: HPDC 2006, France (2006)Google Scholar
  3. 3.
    Vazhkudai, S., Tuecke, S., Foster, I.: Replica Selection in the Globus Data Grid. In: IEEE International Conference on Cluster Computing and the Grid (CCGRID 2001) (2001)Google Scholar
  4. 4.
    Beck, M., Moore, T., Plank, J.S., Swany, M.: Logistical Networking: Sharing More Than the Wires. In: Active Middleware Services Workshop, Norwell, MA (2000)Google Scholar
  5. 5.
    Cohen, B.: BitTorrent web site (2005),
  6. 6.
    Kostic, D., Rodriguez, A., Albrecht, J., Vahdat, A.: Bullet: High Bandwidth Data Dissemination Using an Overlay Mesh. In: SOSP 2003, Lake George, NY (2003)Google Scholar
  7. 7.
    Al-Kiswany, S., Ripeanu, M., Iamnitchi, A., Vazhkudai, S.: Are P2P Data-Dissemination Techniques Viable in Today’s Data Intensive Scientific Collaborations? University of British Columbia (2007)Google Scholar
  8. 8.
    Pendarakis, D., Shi, S., Verma, D., Waldvogel, M.A.: An Application Level Multicast Infrastructure. In: USITS 2001 (2001)Google Scholar
  9. 9.
    Byers, J., Considine, J., Mitzenmacher, M., Rost, S.: Informed Content Delivery Across Adaptive Overlay Networks. In: SIGCOMM 2002, Pittsburg, PA (2002)Google Scholar
  10. 10.
    Ganguly, S., Saxena, A., Bhatnagar, S., Banerjee, S., et al.: Fast Replication in Content Distribution Overlays. In: IEEE INFOCOM, Miami, FL (2005)Google Scholar
  11. 11.
    Enabling Grids for E-sciencE Project (2006)Google Scholar
  12. 12.
    Britton, D., Cass, A.J., Clarke, P.E.L., Coles, J.C., et al.: GridPP: Meeting the Particle Physics Computing Challenge. In: UK e-Science All Hands Conference (2005)Google Scholar
  13. 13.
    Medina, A., Lakhina, A., Matta, I., Byers, J.: BRITE: An Approach to Universal Topology Generation. In: International Workshop on Modeling, Analysis and Simulation of Computer and Telecommunications Systems- MASCOTS 2001, Cincinnati, Ohio (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Samer Al-Kiswany
    • 1
  • Matei Ripeanu
    • 1
  • Adriana Iamnitchi
    • 2
  • Sudharshan Vazhkudai
    • 3
  1. 1.University of British Columbia 
  2. 2.University of South Florida 
  3. 3.Oak Ridge National Laboratory 

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