SPN Model for Web Prefetching and Caching

Shi, Lei; Han, Yinghua; Ding, Xiaoguang; Wei, Lin; Gu, Zhimin

doi:10.1109/skg.2005.116

Cited by 4 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These techniques result in effective document prefetching with efficient buffer size management, but, buffer management can cause additional overhead. Shi et al (2005) propose a new model for integration of web caching and web prefetching called the stochastic petri nets (SPN) model in a server-side proxy. Caching and prefetching are classified into two different categories: passive caching, where only caching takes place, i.e., the accessed documents are stored in the cache for future reference, and local prefetching, where objects are prefetched and cached based only upon the local information available in the client.…”

Section: Related Workmentioning

confidence: 99%

Web caching and prefetching with cyclic model analysis of web object sequences

Srikantaiah

Kumar

Venugopal

et al. 2014

IJKWI

View full text Add to dashboard Cite

Web caching is the process in which web objects are temporarily stored to reduce bandwidth consumption, server load and latency. Web prefetching is the process of fetching web objects from the server before they are actually requested by the client. Integration of caching and prefetching can be very beneficial as the two techniques can support each other. By implementing this integrated scheme in a client-side proxy, the perceived latency can be reduced for not one but many users. In this paper, we propose a new integrated caching and prefetching policy called the WCP-CMA which makes use of a profit-driven caching policy that takes into account the periodicity and cyclic behaviour of the web access sequences for deriving prefetching rules. Our experimental results have shown a 10%-15% increase in the hit ratios of the cached objects and 5%-10% decrease in delay compared to the existing scheme.Keywords: periodicity; sequential pattern analysis; web caching; web log; web prefetching.Reference to this paper should be made as follows: Srikantaiah, K.C., Kumar, N.K., Venugopal, K.R. and Patnaik, L.M. (2014) During the past 35 years of his service at the institute, he has over 700 research publications in refereed international journals and refereed international conference proceedings. He is a fellow of all the four leading science and engineering academies in India. His areas of research interest have been parallel and distributed computing, mobile computing, CAD for VLSI circuits, soft computing and computational neuroscience. This paper is a revised and expanded version of a paper entitled 'An integration of web caching and web prefetching using cyclic behaviour analysis of web sequential patterns' presented at the

show abstract

Section: Related Workmentioning

confidence: 99%

Web caching and prefetching with cyclic model analysis of web object sequences

Srikantaiah

Kumar

Venugopal

et al. 2014

IJKWI

View full text Add to dashboard Cite

show abstract

“…Meanwhile, researchers have found that access to cloud data follows the Zipf-like law [24] and have used this law to design cache and prefetch systems. Shi et al proposed a web prefetching and cache model based on Petri nets, combining prefetching with caching to improve the service quality of distributed storage systems [25].…”

Section: Introductionmentioning

confidence: 99%

Efficient Large-Capacity Caching in Cloud Storage Using Skip-Gram-Based File Correlation Analysis

Xiao,

Yu,

2023

IEEE Access

View full text Add to dashboard Cite

Designing a high-capacity cache is an essential means of improving the accessibility of cloud storage. Compared with traditional data access, cloud storage data access presents new patterns, and traditional caching strategies cannot handle the prefetching and replacement of non-hot data very well. Numerous studies have shown that file correlation can optimize cloud storage's caching and prefetching strategies. However, characterizing the correlation between files from multiple dimensions is quite complex, and the difficulty of optimizing cloud storage caching using file correlation increases accordingly. Based on the above shortcomings, this study designed a file similarity strategy based on skip-gram from the analysis of user access. This strategy completes the prefetching and replacing files in a high-capacity cache by judging the correlation between files. The strategy prefetches files and dynamically inserts them into the cache by judging the correlation between files. After using the prefetching strategy, we significantly improve the cache hit rate in the simulation benchmark. In addition, the strategy can establish an index table after each training completion, which consumes very little time during online operations. During training, the time required to establish the index is O(N * log(V )), and the time for indexing is O(1).INDEX TERMS cache strategy, cloud storage, file correlation, hit rate, machine learning, prefetching.

show abstract