An End-Systems Supported Highly Distributed Content Delivery Network

  • Jaison Paul Mulerikkal
  • Ibrahim Khalil
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4882)


Commercial Content Delivery Networks (CDN) compete each other and are forced to set up costly infrastructure around the globe to effectively deliver Web content to the end-users. Huge financial cost involved in setting up commercial CDN compels the commercial CDN providers to charge high remuneration from their clients (the content providers). Academic models of peer-to-peer CDNs aim to reduce the financial cost of content distribution by forming volunteer group of servers around the globe. But their efficiency is at the mercy of the volunteer peers whose commitment is not ensured in their design. We propose a new architecture that will make use of the existing resources of common Internet users in terms of storage space, bandwidth and Internet connectivity to create a Distributed Content Delivery Network (DCDN). The profit pool generated by the infrastructure savings will be shared among the participating nodes (DCDN surrogates) which will function as an incentive for them to support DCDN.


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  1. 1.
    Molina, B., Ruiz, V., Alonso, I., Palau, C., Guerri, J., Esteve, M.: A closer look at a content delivery network implementation. In: MELECON 2004. Electrotechnical Conference, 2004. Proceedings of the 12th IEEE Mediterranean, Dept. of Commun., Univ. Politecnica de Valencia, Spain, vol. 2, pp. 685–688 (2004)Google Scholar
  2. 2.
    Vakali, A., Pallis, G.: Content distribution networks - status and trends. IEEE Internet Computing, 68–74 (2003)Google Scholar
  3. 3.
    Presti, F., Bartolini, N., Petrioli, C.: Dynamic replica placement and user request redirection in content delivery networks. In: IEEE International Conference on Communications, vol. 3, pp. 1495–1501. Dubrovnik, Los Alamitos (2005)Google Scholar
  4. 4.
    Burns, R., Rees, R., Long, D.: Efficient data distribution in a web server farm. IEEE Internet Computing 5(5), 56–65 (2001)CrossRefGoogle Scholar
  5. 5.
    Pan, C., Atajanov, M., Shimokawa, T., Yoshida, N.: Design of adaptive network against flash crowds. In: Proc. Information Technology Letters, pp. 323–326 (2004)Google Scholar
  6. 6.
    Douglis, F., Kaashoek, M.: Scalable internet services. IEEE Internet Computing 5(4), 36–37 (2001)CrossRefGoogle Scholar
  7. 7.
    Pierre, G., van Steen, M.: Globule: A collaborative content delivery network. IEEE Communications Magazine, 127–133 (2006)Google Scholar
  8. 8.
    Coppens, J., Wauters, T., Turck, F.D., Dhoedt, B., Demeester, P.: Design and performance of a self-organizing adaptive content distribution network. In: IEEE/IFIP Network Operations and Management Symposium 2006, Vancouver, Canada (2006)Google Scholar
  9. 9.
    Dilley, J., Maggs, B., Parlkh, J., Prokop, H., Sitaraman, R., Welhl, B.: Globally distributed content delivery. IEEE Internet Computing, 50–56 (2002)Google Scholar
  10. 10.
    Wikipedia: Content Delivery Networks (cdn) (2007), Web Page:
  11. 11.
    Mahajan, R.: How akamai works (2004), Web Page:
  12. 12.
    Reitz, H.: Cachet Technologies, p. 2163. Harward Business School Publishing, Boston, MA (2000)Google Scholar
  13. 13.
    Pierre, G., van Steen, M.: Design and implementation of a user-centered content delivery network (2003)Google Scholar
  14. 14.
    Sivasubramanian, S., Pierre, B.H.: Globule: a user-centric content delivery network. In: 4th International System Administration and Network Engineering Conference (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Jaison Paul Mulerikkal
    • 1
  • Ibrahim Khalil
    • 1
  1. 1.Distributed Systems and Networking, School of Computer Science, RMIT University, Melbourne 3000Australia

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