Intelligent Web Caching Using Neurocomputing and Particle Swarm Optimization Algorithm

Sulaiman, Sarina; Shamsuddin, Siti Mariyam; Forkan, Fadni; Abraham, Ajith

doi:10.1109/ams.2008.40

Cited by 32 publications

(13 citation statements)

References 4 publications

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“…The oldest noncacheable object is removed first. Intelligent web caching using artificial neural network and particle swarm optimization algorithm [57] trained the network to keep slowly downloading, big and frequently accessed objects in cache. Adaptive web cache predictor [58] utilizes artificial neural network and sliding windows to find whether objects will be reaccessed for at least certain times within the particular number of following accesses.…”

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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“…They generally perform better than the basic caching schemes. The adaptive and intelligent caching schemes estimate the grading value by using the request statistics, network information and web server's capacity, which utilizes statistical or machine learning techniques (Sulaiman et al 2008;Cobb and ElAarag 2008;Yang and Zhang 2003). The grading value used in these methods captures the traffic dynamics better, but with more computational overhead.…”

Section: Introductionmentioning

confidence: 99%

“…These methods are not applicable if the traffic nature is dynamic. To tackle this situation, researchers adopted intelligent and heavy machine learning techniques in the form of neural networks (NN) (Cobb and ElAarag 2008), artificial intelligence (AI) (Sulaiman et al 2008) and web log mining technique (Yang and Zhang 2003) for which the computational overheads are high. Also, the practical feasibility of such methods is yet to be established.…”

Section: Introductionmentioning

confidence: 99%

A novel content classification scheme for web caches

Sajeev

Sebastian

2010

Evolving Systems

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Web caches are useful in reducing the user perceived latencies and web traffic congestion. Multi-level classification of web objects in caching is relatively an unexplored area. This paper proposes a novel classification scheme for web cache objects which utilizes a multinomial logistic regression (MLR) technique. The MLR model is trained to classify web objects using the information extracted from web logs. We introduce a novel grading parameter worthiness as a key for the object classification. Simulations are carried out with the datasets generated from real world trace files using the classifier in Least Recently Used-Class Based (LRU-C) and Least Recently Used-Multilevel Classes (LRU-M) cache models. Test results confirm that the proposed model has good online learning and prediction capability and suggest that the proposed approach is applicable to adaptive caching.

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“…There are three important advantages of Web caching such as reduced bandwidth consumption, reduced server load and reduced latency. These benefits have made the Web less costly with better performance, Sulaiman et al, (2008) proposed an Artificial Intelligence (AI) approach for Web caching to find the type of Web request, either to cache or not, and to optimize the performance on Web cache. Two approaches are used in this study; Artificial Neural Network (ANN), and Particle Swarm Optimization (PSO).…”

Section: Related Workmentioning

confidence: 99%

Optimized semantic based multiple web search engine with anti-phishing technique

2016

Rev. Téc. Ing. Univ. Zulia.

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Searching is one of the operations used commonly on the Internet. Search engine, a tool for searching, are extremely popular and recurrently used sites. There are billions of pages on the Web where it is not possible to search all the related websites manually. However, most well-known search engines return results having many pages that are absolutely useless for the user. The security and authentication of the web pages in the websites is also a challenging and an important issue in the current scenario. Phishing is a social crime which affects the privacy and security of the users. Nowadays, this social crime has been increasing as the World Wide Web is becoming more and more popular. This research mainly deals with three proposed approaches for the design of effective and secure search engine. They are (i) Semantic Based Multiple Web Search Engine(ii)Web Caching and Response Time Optimization Based On Eviction Method (ii)Detection Of Phishing Web Pages Based On Image Processing Techniques. The proposed approaches were evaluated on the java platform to determine their performance. Thus the semantic approach is very significant in terms of search accuracy. The time complexity is also reduced greatly in this approach. The searches take place simultaneously from different search engines, and the searches do not have to wait for each search engine, the results are computed simultaneously from multiple search engines and they are displayed on the screen. The result is therefore much faster.Keywords: Multisearch engines; XML; resource description framework; ontology; semantic web INTRODUCTIONSearching is one of the operations used commonly on the Internet. Search engine (Brin et al., 1998) a tool for searching, are extremely popular and recurrently used sites. Consider a card catalogue in a library. There exist a volumness and helpful information, but it is physically not possible to check all the books personally for finding particular information. Similarly, there are billions of pages on the Web; it is not possible to search all the related websites manually. Thus, the explosive growth and remarkable development of information offered to end users through the Web has made the search engine approach to play a key role.At present, search engines comprise mainly, useful tools for arranging information and extracting knowledge from the Web. However, it is not exceptional that still the most well-known search engines return results having many pages that are absolutely useless for the user. This is mostly because of the fact that fundamental relevance criterions underlying their information retrieval strategies focus on the existence of query keywords within the returned pages. However, because of their common-purpose approach, gives unrelated results that provide a group of useless pages.

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Intelligent Web Caching Using Neurocomputing and Particle Swarm Optimization Algorithm

Cited by 32 publications

References 4 publications

Multi-provider cloud computing network infrastructure optimization

Multi-provider cloud computing network infrastructure optimization

A novel content classification scheme for web caches

Optimized semantic based multiple web search engine with anti-phishing technique

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