Adaptive Policies in Information Lifecycle Management

  • Rohit M. Lotlikar
  • Mukesh Mohania
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4080)


Adaptive policies contain parameters and take into consideration performance feedback to modify values of these parameters adaptively. We propose a method (applicable to the domain of Information Lifecycle Management) to automatically adapt these parameters. Design issues such as selection of sensors, desired ranges for sensors and effects of parameter sensitivity such as over-correction and under-correction are discussed.


Archive Record Table Size Adaptation Rule Cache Replacement Policy Parameter 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Masullo, M.J., Calo, S.B.: Policy management: An architecture and approach. In: Proceedings of the IEEE First International Workshop on Systems Management, pp. 13–26. ACM Press, New York (1993)CrossRefGoogle Scholar
  2. 2.
    Ashton, L.L., Baker, E.A., Bariska, A.J., Dawson, E.M., Ferziger, R.L., Kissinger, S.M., Menendez, T.A., Shyam, S., Strickland, J.P., Thompson, D.K., Wilcock, G.R., Wood, M.W.: Two decades of policy-based storage management for the ibm mainframe computer. IBM Syst. J. 42(2), 302–321 (2003)CrossRefGoogle Scholar
  3. 3.
    Zhang, Y., Hakozaki, K., Kameda, H., Shimizu, K.: A performance comparison of adaptive and static load balancing in heterogeneous distributed systems. In: 28th Annual Simulation Symposium, vol. 332. IEEE Press, Los Alamitos (1995)Google Scholar
  4. 4.
    Podlipnig, S., Boszormenyi, L.: A survey of web cache replacement strategies. ACM Comput. Surv. 35(4), 374–398 (2003)CrossRefGoogle Scholar
  5. 5.
    Ogata, K.: Modern Control Engineering. Prentice Hall Professional Technical Reference (2001)Google Scholar
  6. 6.
    Diao, Y., Hellerstein, J., Parekh, S.: Using fuzzy control to maximize profits in service level management. IBM Syst. J. 41(3), 403–420 (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Rohit M. Lotlikar
    • 1
  • Mukesh Mohania
    • 2
  1. 1.IBM India Research Lab-BangaloreBangaloreIndia
  2. 2.IBM India Research Lab-DelhiHauz Khas, New DelhiIndia

Personalised recommendations