CFP last date
20 March 2024
Reseach Article

A Review on Adaptive Web Caching Technique

by Pranay Nanda, Shamsher Singh, G. L. Saini
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 133 - Number 12
Year of Publication: 2016
Authors: Pranay Nanda, Shamsher Singh, G. L. Saini

Pranay Nanda, Shamsher Singh, G. L. Saini . A Review on Adaptive Web Caching Technique. International Journal of Computer Applications. 133, 12 ( January 2016), 25-30. DOI=10.5120/ijca2016908043

@article{ 10.5120/ijca2016908043,
author = { Pranay Nanda, Shamsher Singh, G. L. Saini },
title = { A Review on Adaptive Web Caching Technique },
journal = { International Journal of Computer Applications },
issue_date = { January 2016 },
volume = { 133 },
number = { 12 },
month = { January },
year = { 2016 },
issn = { 0975-8887 },
pages = { 25-30 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2016908043 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T23:30:59.538733+05:30
%A Pranay Nanda
%A Shamsher Singh
%A G. L. Saini
%T A Review on Adaptive Web Caching Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 133
%N 12
%P 25-30
%D 2016
%I Foundation of Computer Science (FCS), NY, USA

Traditional caches see a fixed-size page; a Web cache, on the other hand, sees complete objects (text files, images, or video clips), which vary considerably in size. In addition, a traditional cache deals with addresses, while a Web cache can potentially deduce more contextual information from its objects. Web objects are predominantly read-only, taking implementation of cache coherence easier. The response times of Web accesses are in the order of seconds (versus milliseconds for system access), which allows for more elaborate caching algorithms. Finally, a Web cache encounters more dimensions of dependence than are taken into account by traditional methods. Primary cache replacement algorithms consider arrival time as the only one factor as the basis of their functionality. They disregard parameters such as page size, fetching delay, reference rate, and invalidation cost and invalidation frequency of a web object. Considering these parameters produces better and more apt results with greater efficiency, thereby surpassing traditional and conventional algorithms such as LRU, LIFO and LFU in performance and accuracy. Most of them are favorable to objects with homogenous sizes. Also, many of these algorithms depend on manual interference to find quick cures for symptoms instead of understanding the core issues. Because the cache space is limited and no technology can be as suitable to cater to each user’s request separately, we need caching algorithms that are intelligent and adapt to the available resources and utilize them optimally. Systems must evolve towards more scalable, adaptive, efficient and self-configuring web caching systems to effectively support the phenomenal growth in demand for web content on the internet. Adaptive caching views caching problems as a way of optimizing global data dissemination. Studies have shown that adaptive algorithms yield better results than conventional caching algorithms.

  1. Achuthsankar S. Nair, J.S. Jayasudha, “Improving Performance by World Wide Web by Adaptive Web Traffic Reduction”, Proceedings of World Academy of Science, Engineering and Technology, Volume 17, December 2006
  2. Anish Kumar Saha, Partha Pratim Deb, Moutishi Kar, D. Rudrapal, “An optimization technique of web caching using Fuzzy Inference System”, International Journal of Computer Applications, Volume 43-No.17, April, 2012
  3. Annie P. Foong, Yu-Hen Hu and Dennis M. Heisey, “Adaptive web caching using logistic regression”, IEEE, 1999
  4. Athena Vakali, George Pallis, “A study on web caching architectures and performance”
  5. Dhawaleswar Rao. CH, “Study of the web caching Algorithms for Performance Improvement of the response speed”, Indian Journal of Computer Science and Engineering”, Volume 3 – No. 2, April-March, 2012
  6. Farhan Mohamed, Abdul Samad Ismail, Siti Mariyam Shamsuddin, “Web caching and prefetching: Techniques and analysis in World Wide Web”, Proceedings of the Postgraduate Annual Research Seminar, 2005
  7. Hossam Hassanein, Zhengang Liang and Patrick Martin, “Performance comparison of Alternative Web Caching Techniques”, Proceedings of the Seventh International Symposium on Computers and Communications, 2002
  9. Ismail Ari, Ahmed Amer, Robert Gramacy, Ethan L.Miller, Scott A. Brandt, Darrell D.E. Long, “ACME: Adaptive Caching using Multiple Experts”
  10. Lixia Zhang, Sally Floyd and Van Jacobson, “Adaptive Web Caching”, April 25, 1997
  11. S.Sulaiman, Siti Mariyam Shamsuddin and A.Abraham, “Intelligent web caching using Adaptive Regression Trees, Splines, Random Forests and Tree Net”
  12. Scott Michel, Lixia Zhang, Sally Floyd, “Adaptive web caching: Towards a new global caching architecture”, Computer Networks and ISDN Networks, November 1998
  13. Sean C. Rhea, Kevin Liang, Eric Brewer, “Value based web Caching”, May 20-24, 2003
  14. Waleed Ali, Siti Mariyam Shamsuddin, “Neuro-fuzzy system in partitioned client-side web cache”, Expert systems with applications, November 2011
  15. Waleed Ali, Siti Mariyam, Shamsuddin, Abdul Samad Ismail, “A Survey of Web caching and Prefetching”, International Journal of Advanced Soft Computing Applications, Volume 3- No. 1, March 2011
  16. Yun Ji Na, Choon Seong Leem, Il Seok Ko, “ACASH: an adaptive web caching method based on the heterogeneity of web object and reference characteristics”, Information Sciences, May 20, 2005
Index Terms

Computer Science
Information Sciences


Web Caching Caching Cache Algorithm.