An Approach for Web Pre-fetching to Enhance User Interaction of Web Application Using Markov Model

Pal, Monti Babulal; Jain, Dinesh Chandra

doi:10.1109/csnt.2014.80

Cited by 4 publications

(1 citation statement)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Pattern recognition and machine learning have been increasingly used for cache replacement policies as well as prefetching. For instance, Pal and Jain [18] proposed a prefetching mechanism for web browsing that uses Markov models to predict which pages the users will request next. On another reported case, Garcia et al [19] used neural networks to predict the part of the map would be needed next, for map and navigation services.…”

Section: B Cache and Prefetchingmentioning

confidence: 99%

An Intelligent Cloud Storage Gateway for Medical Imaging

et al. 2017

View full text Add to dashboard Cite

Abstract-Historically, medical imaging repositories have been supported by indoor infrastructures. However, the amount of diagnostic imaging procedures has continuously increased over the last decades, imposing several challenges associated with the storage volume, data redundancy and availability. Cloud platforms are focused on delivering hardware and software services over the Internet, becoming an appealing solution for repository outsourcing. Although this option may bring financial and technological benefits, it also presents new challenges. In medical imaging scenarios, communication latency is a critical issue that still hinders the adoption of this paradigm.This paper proposes an intelligent Cloud storage gateway that optimizes data access times. This is achieved through a new cache architecture that combines static rules and pattern recognition for eviction and prefetching.The evaluation results, obtained through simulations over a real-world dataset, show that cache hit ratios can reach around 80%, leading reductions of image retrieval times by over 60%.The combined use of eviction and prefetching policies proposed can significantly reduce communication latency, even when using a small cache in comparison to the total size of the repository. Apart from the performance gains, the proposed system is capable of adjusting to specific workflows of different institutions.

show abstract

Section: B Cache and Prefetchingmentioning

confidence: 99%