ENHANCED WEB CACHE REPLACEMENT POLICY BASED ON DATA MINING AND RFSD SCORING

Year 2017, , 293 - 298, 30.06.2017

Edris Rajaby Tugrul Cavdar

https://doi.org/10.17261/Pressacademia.2017.603

Abstract

By rapid growth of the Internet users and devices, the
number of servers also increase simultaneously which causes the exponential
increment of the internet traffic and static data. Handling these huge amounts
of user requests and efficiently responding to them require high bandwidth
links, powerful servers and robust equipment, which despite the availability of
these requirements getting the full user satisfaction is extremely difficult
and a tough challenge. In order to overcome the mentioned problem, the cache
servers are being used as a suitable solution. The performance of web cache
server directly depends on its replacement policies. Several cache replacement
policies have been proposed in literature each having varied hit rate (HR) and
byte hit rate (BHR) performances on different networks. The replacement policy
proposed in this paper is a dynamic cache replacement policy which trains
itself utilizing previous network logs and by exploiting the data mining
clustering algorithm. Once the training step is completed, the proposed policy
utilizes the normalization formulas to score each metric of the enquiries
including recency, frequency, size and delay. Simulation results showed that
the proposed policy has the optimum performance on different networks and it
not only improved the performance of web cache server in term of HR and BHR,
but also decreases the data retrieval time (Delay Ratio (DR)) of the cache
servers.  

Keywords

cache replacement policy, cache server, proxy server, scoring

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