LRU-based algorithms for Web Cache Replacement

  • A. I. Vakali
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1875)


Caching has been introduced and applied in prototype and commercial Web-based information systems in order to reduce the overall bandwidth and increase system’s fault tolerance. This paper presents a track of Web cache replacement algorithms based on the Least Recently Used (LRU) idea. We propose an extension to the conventional LRU algorithm by considering the number of references to Web objects as a critical parameter for the cache content replacement. The proposed algorithms are validated and experimented under Web cache traces provided by a major Squid proxy cache server installation environment. Cache and bytes hit rates are reported showing that the proposed cache replacement algorithms improve cache content.


Web-based information systems Web caching and proxies Cache replacement algorithms Cache consistency 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    C. Aggarwal, J. Wolf and P.S. Yu: Caching on the World Wide Web, IEEE Transactions on Knowledge and Data Engineering, Vol. 11, No. 1,pp. 94–107,Jan-Feb 1999.CrossRefGoogle Scholar
  2. 2.
    M. Arlitt, R. Friedrich and T. Jin: Performance Evaluation of Web Proxy Cache Replacement Policies, Hewlett-Packard Technical Report HPL 98-97, to appear: Performance Evaluation Journal, May 98.Google Scholar
  3. 3.
    A. Belloum and L.O. Hertzberger: Document Replacement Policies dedicated to Web Caching, Proceedings ISIC/CIRA/ISAS’98 Conference, Maryland, USA, Sep. 1998.Google Scholar
  4. 4.
    R. Caceres, F. Douglis, A. Feldmann, C. Glass, M. Rabinovich: Web Proxy Caching: The Devil is in the Details, Proceedings of the SIGMETRICS Workshop on Internet Server Performance, Jun 1998.Google Scholar
  5. 5.
    P. Cao, J. Zhang and K. Beach: Active Cache: Caching Dynamic Contents on the Web, Proceedings of the IFIP International Conference on Distributed Platforms and Open Distributed Processing, pp. 373–388, Middleware 1998.Google Scholar
  6. 6.
    A. Chankhunthod, P. Danzig and C. Neerdaels: A Hierarchical Internet Object Cache, Proceedings of the USENIX 1996 Annual Technical Conference, pp. 153–163,San Diego,California, Jan 1996.Google Scholar
  7. 7.
    S. Michel, K. Nguyen, A. Rosenstein and L. Zhang: Adaptive Web Caching: Towards a New Global Caching Architecture, Proceedings of the 3rd International WWW Caching Workshop, Manchester, England, Jun 1998.Google Scholar
  8. 8.
    A Distributed Testbed for National Information Provisioning,, 1998.
  9. 9.
    M. Nottingham: Web Caching Documentation,, Nov 1998.
  10. 10.
    E. J. O’Neil, P.E. O’Neil, and G. Weikum: The LRU-K Page Replacement Algorithm For Database Disk Buffering, Proceedings of the ACM SIGMOD Conference, pp. 297–306, Washington DC, USA, 1993.Google Scholar
  11. 11.
    Squid: Squid Internet Object Cache, mirror site, Aristotle UNiversity,, 1999.
  12. 12.
    A. Vakali: A Web-based evolutionary model for Internet Data Caching, Proceedings of the 2nd International Workshop on Network-Based Information Systems, NBIS’99,IEEE Computer Society Press, Florence, Italy, Aug 1999.Google Scholar
  13. 13.
    A. Vakali: A Genetic Algorithm scheme for Web Replication and Caching, Proceedings of the 3rd IMACS/IEEE International Conference on Circuits, Systems, Communications and Computers, CSCC’99, World Scientific and Engineering Society Press, Athens, Greece, Jul. 1999.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • A. I. Vakali
    • 1
  1. 1.Department of InformaticsAristotle University of ThessalonikiGreece

Personalised recommendations