Universiti Teknologi Malaysia Institutional Repository

Integration of least recently used algorithm and neuro-fuzzy system into client-side web caching

Ali, Waleed and Shamsuddin, Siti Mariyam (2009) Integration of least recently used algorithm and neuro-fuzzy system into client-side web caching. International Journal of Computer Science and Security, 3 (1). pp. 1-15. ISSN 1985-1553

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Web caching is a well-known strategy for improving performance of Web-based system by keeping web objects that are likely to be used in the near future close to the client. Most of the current Web browsers still employ traditional caching policies that are not efficient in web caching. This research proposes a splitting client-side web cache to two caches, short-term cache and long-term cache. Initially, a web object is stored in short-term cache, and the web objects that are visited more than the pre-specified threshold value will be moved to long-term cache. Other objects are removed by Least Recently Used (LRU) algorithm as short-term cache is full. More significantly, when the long-term cache saturates, the neuro-fuzzy system is employed in classifying each object stored in long-term cache into either cacheable or uncacheable object. The old uncacheable objects are candidate for removing from the long-term cache. By implementing this mechanism, the cache pollution can be mitigated and the cache space can be utilized effectively. Experimental results have revealed that the proposed approach can improve the performance up to 14.8% and 17.9% in terms of hit ratio (HR) compared to LRU and Least Frequently Used (LFU). In terms of byte hit ratio (BHR), the performance is improved up to 2.57% and 26.25%, and for latency saving ratio (LSR), the performance is improved up to 8.3% and 18.9%, compared to LRU and LFU

Item Type:Article
Additional Information:This is an open access journal
Uncontrolled Keywords:client-side web caching, adaptive neuro-fuzzy inference system, least recently used algorithm
Subjects:Q Science > Q Science (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System (Formerly known)
ID Code:11827
Deposited By: Siti Anisa Abdul Hamid
Deposited On:19 Jan 2011 12:29
Last Modified:18 Feb 2017 01:20

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