Intelligent Client-Side Web Caching Scheme Based on Least Recently Used Algorithm and Neuro-Fuzzy System

Ali, Waleed; Shamsuddin, Siti Mariyam

doi:10.1007/978-3-642-01510-6_9

Cited by 34 publications

(10 citation statements)

References 9 publications

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“…A lower rating score represents a better choice for replacement. Intelligent long-term cache removal algorithm based on adaptive neuro-fuzzy inference system (ANFIS) [56] takes access frequency, recency, object size and downloading latency as the inputs of a trained ANFIS to dictate noncacheable objects. In ANFIS training, objects requested again at later point in specific time are considered cacheable.…”

Section: Object Cacheabilitymentioning

confidence: 99%

Multi-provider cloud computing network infrastructure optimization

Banditwattanawong

Masdisornchote

Uthayopas

2016

Future Generation Computer Systems

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h i g h l i g h t s• Byte-hit rate and hit rate could be optimal simultaneously in a nonuniform cost model. • i-Cloud outperformed popular LRU, GDSF and LFUDA schemes in a nonuniform cost environment.• i-Cloud's performances were stable and close to those of infinite cache size. • Window size had small performance effect when relative cache sizes were big.• Accounting data-out charge rates improved all performance aspects at small cache sizes. a b s t r a c tCloud-adopting enterprises have been increasingly employing multiple cloud providers concurrently, for example, to consume unique services and to mitigate data lock-in risk. As a consequence, the enterprises must be able to address contrasting quality-of-service degrees offered by the different providers. This paper presents an intelligent cloud cache eviction approach, namely i-Cloud, as the core component of a client-side cloud cache. i-Cloud is capable of reducing public cloud data-out expenses, improving cloud network scalability and lowering cloud service access latencies specifically in multi-provider cloud environments. Trace-driven simulations have shown that i-Cloud outperformed well-known approaches in all performance metrics. In addition, i-Cloud is not only able to achieve optimal performances in all metrics simultaneously but also delivered relatively stable performances across all performance metrics. The results have also indicated that taking the nonuniformity of data-out charge rates into cache eviction decisions improved caching performances in all metrics.

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Section: Object Cacheabilitymentioning

confidence: 99%

Multi-provider cloud computing network infrastructure optimization

Banditwattanawong

Masdisornchote

Uthayopas

2016

Future Generation Computer Systems

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“…In [3], an Adaptive Neuro-Fuzzy Inference System (AN-FIS) has been applied to predict web objects that would be revisited again. The simulation results demonstrate that the proposed approach improves the performance in terms of HR; while, the performance in terms of BHR was not good enough because the proposed approach does not consider the size and the cost of the predicted objects in cache replacement decisions.…”

Section: Related Workmentioning

confidence: 99%

Intelligent Cooperative Least Recently Used Web Caching Policy based on J48 Classifier

Yasin

Ibrahim

Udzir

et al. 2014

Proceedings of the 16th International Conference on Information Integration and Web-Based Applications &Amp; Services

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Web caching plays a key role in delivering web objects to the end-users which is one of the advantages of World Wide Web (WWW). However, the size of the cache is limited which is considered as one of the drawbacks of web caching. Furthermore, retrieving the same web object from the origin server many times consumes the network bandwidth. Moreover, cache pollution is a drawback of traditional web caching policies such as Least Recently Used (LRU) web caching policy where web objects that are stored in the cache are not visited frequently. In this work, new intelligent cooperative web caching approach based on J48 classifier is presented. A simulation is carried out to evaluate the performance of the proposed approach. The results show that the new approach improves the performance of the LRU web caching policy.

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“…More details about intelligent Web caching approaches are given in [15]. In [16], the client-side cache has been divided into two caches namely short-term cache and long-term cache. In NNPCR [17] and NNPCR-2 [18], back-propagation neural network (BPNN) has been used for making cache replacement decision.…”

Section: Web Proxy Server Caching Algorithmsmentioning

confidence: 99%

A Novel Probability based Approach for Optimized Prefetching

Panwar¹,

Jain

Kumar

2016

IJIEEB

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As the World Wide Web carries on to grow up rapidly in size and popularity, web traffic and network bottlenecks are more important issues in the networked world. The continued enhancement in demand for items on the World Wide Web causes severe overloading in many sites, network congestion, delay in perceived latency and network bottleneck. Many users have no patience in waiting more than a few seconds for downloading a web page, that's why Web traffic reduction system is very necessary in today World Wide Web for accessing the websites efficiently with the facility of existing networks. Web caching is an effective method to improve the performance of the World Wide Web but in today's World Wide Web caching method alone is not enough because of World Wide Web has grown quickly from a simple information-sharing mechanism to a rich collection of dynamic objects and multimedia data. The web prefetching is used to improve the performance of the proxy server. Prefetching predict web object that is expected to be requested in the near future and store them in advance, thus the response time of the user request is reduced. To improve the performance of the proxy server, this paper proposed a new framework which combines the caching system and prefetching technique and also optimize the prefetching with the help of probability. In this paper, we use the dataset for the experiment which is collected from ircache.net proxy server and give the result with the comparison of other technique of prefetching.

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Intelligent Client-Side Web Caching Scheme Based on Least Recently Used Algorithm and Neuro-Fuzzy System

Cited by 34 publications

References 9 publications

Multi-provider cloud computing network infrastructure optimization

Multi-provider cloud computing network infrastructure optimization

Intelligent Cooperative Least Recently Used Web Caching Policy based on J48 Classifier

A Novel Probability based Approach for Optimized Prefetching

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