An improved web caching system with locally normalized user intervals
Locally normalized intervals; pre-fetching; proxy; web cache
Caching is one of the most promising areas in the field of future internet architecture like Information-centric Networking, Software Defined Networking, and IoT. In Web caching, most of the web content is readily available across the network, even if the webserver is not reachable. Several existing traditional caching methods and cache replacement strategies are evaluated based on the metrics like hit ratio and byte hit Ratio. However, these metrics have not been improved over the period because of the traditional caching policies. So, in this paper, we have used an intelligent function like locally normalized intervals of page visit, website duration, users' interest between user groups is proposed. These intervals are combined with multiple distance metrics like Manhattan, squared Euclidean, and 3-,4-,5-norm Minkowski. In order to obtain significant common user navigation patterns, the clustering relation between the users using different intervals and distances is thoroughly analyzed. These patterns are successfully coupled with greedy web cache replacement strategies to improve the efficiency of the proposed web cache system. Particularly for improving the caching metrics more, we used an AI-based intelligent approach like Random Forest classifier to boost the prefetch buffer performance and achieves the maximum hit rate of 0.89, 0.90, and byte hit rate of 0.87, 0.89 for Greedy Dual Size Frequency and Weighted Greedy Dual Size Frequency algorithms, respectively. Our experiments show good hit/byte hit rates than the frequently used algorithms like least recently used and least frequently used. 2013 IEEE.
Vaithinathan K.; Pernabas J.B.; Parthiban L.; Shrestha B.; Joshi G.P.; Moon H.
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ACCESS.2021.3103804 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113251855&doi=10.1109%2fACCESS.2021.3103804&partnerID=40&md5=7c7ad1f86343b42869b4d8b09bd9b1c9
Vaithinathan K., Department of Computer Engineering, Karaikal Polytechnic College, Karaikal, 609609, India; Pernabas J.B., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to Be University), Kengeri Campus, Karnataka, Bangalore, 560074, India; Parthiban L., Department of Computer Science and Engineering, Community College, Pondicherry University, Puducherry, 605014, India; Shrestha B., Department of Information Contents, Kwangwoon University, Seoul, 01897, South Korea; Joshi G.P., Department of Computer Science and Engineering, Sejong University, Seoul, 05006, South Korea; Moon H., Department of Computer Science and Engineering, Sejong University, Seoul, 05006, South Korea