Content Distribution Through Autonomic Content and Storage Management

  • Nikolaos Laoutaris
  • Antonios Panagakis
  • Ioannis Stavrakakis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3457)


Content Distribution has to date been addressed by a mix of centralized and uncoordinated distributed processes, such as server replication and traditional node caching mechanisms, respectively. It is an inherently distributed process that is also increasingly relying on entities that are not only increasingly distributed but also increasingly autonomous. Consequently, centralized – and typically targeting the “socially optimal” – decisions are rather unrealistic for a distributed environment of autonomic entities. Instead, a distributed management of the engaged autonomic entities, which take decisions dynamically, should be key to efficient content distribution. The latter is advocated in this paper in which two entities that are central to content distribution – specifically the content and the node storage – are considered and it is discussed how their autonomic behavior drives the operation of a content distribution network. In the first case, it is the content that manages itself by dynamically generating duplicate copies and pushing them to (seizing) the appropriate storage. In the second one, it is the node storage that is in charge, deciding on the content to be locally stored. The decisions taken by the distributed and autonomic entities may – in the extreme case – be driven by self-awareness and self-interest only, without any network state information and co-operativeness. Or, they may use (some) network information and take decisions in a more cooperative manner, despite their autonomic and self-interest-driven nature. An example is presented on the later case, showing the potential both social and individual benefits.


Content Distribution Socially Optimal Storage Management Node Storage Social Utility 
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.


  1. 1.
    Antoniadis, P., Courcoubetis, C., Mason, R.: Comparing economic insentives in peer-to-peer networks. Computer Networks 46(1), 1–146 (2004)CrossRefGoogle Scholar
  2. 2.
    Baev, I.D., Rajaraman, R.: Approximation algorithms for data placement in arbitrary networks. In: Proceedings of the 12th Annual Symposium on Discrete Algorithms (ACM-SIAM SODA), pp. 661–670 (January 2001)Google Scholar
  3. 3.
    Chun, B.-G., Chaudhuri, K., Wee, H., Barreno, M., Papadimitriou, C.H., Kubiatowicz, J.: Selfish caching in distributed systems: A game-theoretic analysis. In: Proc. ACM Symposium on Principles of Distributed Computing (ACM PODC), Newfoundland, Canada (July 2004)Google Scholar
  4. 4.
    Cronin, E., Jamin, S., Jin, C., Kurc, A.R., Raz, D., Shavitt, Y.: Constraint mirror placement on the internet. IEEE Journal on Selected Areas in Communications 20(7) (2002)Google Scholar
  5. 5.
    Fan, L., Cao, P., Almeida, J., Broder, A.Z.: Summary cache: a scalable wide-area web cache sharing protocol. IEEE/ACM Transactions on Networking 8(3), 281–293 (2000)CrossRefGoogle Scholar
  6. 6.
    Gibson, G.A., Van Meter, R.: Network attached storage architecture. Communications of the ACM 43(11), 37–45 (2000)CrossRefGoogle Scholar
  7. 7.
    Hadjiefthymiades, S., Georgiadis, Y., Merakos, L.: A game theoretic approach to web caching. In: Proceedings of IFIP Networking 2004, Athens, Greece (May 2004)Google Scholar
  8. 8.
    IBM Corp. Autonomic Computing initiative (2002),
  9. 9.
    Kangasharju, J., Roberts, J., Ross, K.W.: Object replication strategies in content distribution networks. Computer Communications 25(4), 376–383 (2002)CrossRefGoogle Scholar
  10. 10.
    Korupolu, M.R., Plaxton, C.G., Rajaraman, R.: Placement algorithms for hierarchical cooperative caching. In: Proceedings of the 10th Annual Symposium on Discrete Algorithms (ACM-SIAM SODA), pp. 586–595 (1999)Google Scholar
  11. 11.
    Laoutaris, N., Zissimopoulos, V., Stavrakakis, I.: Distributed selfish replication (2004) [submitted]Google Scholar
  12. 12.
    Laoutaris, N., Zissimopoulos, V., Stavrakakis, I.: Joint object placement and node dimensioning for internet content distribution. Information Processing Letters 89(6), 273–279 (2004)zbMATHCrossRefMathSciNetGoogle Scholar
  13. 13.
    Laoutaris, N., Zissimopoulos, V., Stavrakakis, I.: On the optimization of storage capacity allocation for content distribution. Computer Networks (2005) [to appear]Google Scholar
  14. 14.
    Leff, A., Wolf, L., Yu, P.S.: Replication algorithms in a remote caching architecture. IEEE Transactions on Parallel and Distributed Systems 4(11), 1185–1204 (1993)CrossRefGoogle Scholar
  15. 15.
    Li, B., Golin, M.J., Italiano, G.F., Deng, X., Sohraby, K.: On the optimal placement of web proxies in the internet. In: Proceedings of the Conference on Computer Communications (IEEE Infocom), New York (March 1999)Google Scholar
  16. 16.
    Li, J., Reiher, P.L., Popek, G.J.: Resilient self-organizing overlay networks for security update deliver. IEEE Journal on Selected Areas in Communications 22(1), 189–202 (2004)CrossRefGoogle Scholar
  17. 17.
    Pan, J., Hou, Y.T., Li, B.: An overview DNS-based server selection in content distribution networks. Computer Networks 43(6) (December 2003)Google Scholar
  18. 18.
    Qiu, L., Padmanabhan, V., Voelker, G.: On the placement of web server replicas. In: Proceedings of the Conference on Computer Communications (IEEE Infocom), Anchorage, Alaska (April 2001)Google Scholar
  19. 19.
    Saroiu, S., Gummadi, K.P., Dunn, R.J., Gribble, S.D., Levy, H.M.: An analysis of internet content delivery systems. In: Proceedings of the 5th Symposium on Operating Systems Design and Implementation (OSDI 2002) (December 2002)Google Scholar
  20. 20.
    Stoica, I., Morris, R., Liben-Nowell, D., Karger, D.R., Kaashoek, M.F., Dabek, F., Balakrishnan, H.: Chord: A scalable peer-to-peer lookup protocol for internet applications. IEEE/ACM Transactions on Networking 11(1), 17–32 (2003)CrossRefGoogle Scholar
  21. 21.
    Turner, D.A., Ross, K.W.: A lightweight currency paradigm for the P2P reseource market (2003) [submitted work]Google Scholar
  22. 22.
    Wessels, D., Claffy, K.: ICP and the Squid web cache. IEEE Journal on Selected Areas in Communications 16(3) (April 1998)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Nikolaos Laoutaris
    • 1
  • Antonios Panagakis
    • 1
  • Ioannis Stavrakakis
    • 1
  1. 1.Department of Informatics and TelecommunicationsUniversity of AthensAthensGreece

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