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http://hdl.handle.net/10603/251831
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DC Field | Value | Language |
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dc.coverage.spatial | Hit ratio and byte hit ratio by combining intelligent web caching with web Pre-fetching techniques | |
dc.date.accessioned | 2019-08-01T05:24:15Z | - |
dc.date.available | 2019-08-01T05:24:15Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/251831 | - |
dc.description.abstract | Internet has become the universal source of information for billions of people at homes at educational institutions, and at workplaces The number of Internet users is continuing to be on the rise and is expected to cross 50% of the world population in the next few years Internet users experience significant delay in access to information due to this enormous growth in web trafficTo overcome this delay the frequently accessed information may be maintained in a location nearer to the user typically in a cache memory As the cache size is limited efficient replacement techniques have to be deployed when the cache becomes full Hit RatioHR and Byte Hit Ratio BHR are the two parameters used to analyze the efficiency of web caching techniques Web caching is the process of maintaining copies of web objects in the cache memory that are available in the original server thereby having the distinct advantage of serving the user requests immediately Web prefetching is a techniquenthat is used to preload the yet to be requested web objects with an expectation that a user will be requesting it in the future In the literature survey carried out many works for improving HR and BHR have been implemented by considering web caching and web pre fetching techniques individually For web caching traditional page replacement techniques like Least Recently Used LRU and Least Frequently Used LFU are considered by researchers By considering intelligent web caching techniques researchers have demonstrated improved performance in terms of HR and BHR In this proposed work it is demonstrated that by combining intelligent web caching techniques with web pre fetching technique, the HR and BHR are significantly improved In this research LRU Support Vector Machine SVM Bayesian and Neurofuzzy techniques are used for web caching. Clustering and Spatial Weight Matrix SWM methods are used individually for web pre fetching In clustering, both inter-site and intra site clustering are considered newline | |
dc.format.extent | xix, 127p. | |
dc.language | English | |
dc.relation | p.117-126 | |
dc.rights | university | |
dc.title | Certain investigations on improving hit ratio and byte hit ratio by combining intelligent web caching with web pre fetching techniques | |
dc.title.alternative | ||
dc.creator.researcher | Vijilesh V | |
dc.subject.keyword | Byte Hit Ratio | |
dc.subject.keyword | Engineering and Technology,Computer Science,Computer Science Theory and Methods | |
dc.subject.keyword | Hit Ratio | |
dc.subject.keyword | Intelligent Web Caching | |
dc.subject.keyword | Web Pre-Fetching Techniques | |
dc.description.note | ||
dc.contributor.guide | Nedunchezhian R | |
dc.publisher.place | Chennai | |
dc.publisher.university | Anna University | |
dc.publisher.institution | Faculty of Information and Communication Engineering | |
dc.date.registered | n.d. | |
dc.date.completed | 2017 | |
dc.date.awarded | 31/07/2017 | |
dc.format.dimensions | 21 cm | |
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 55.37 kB | Adobe PDF | View/Open |
02_certificates.pdf | 211.34 kB | Adobe PDF | View/Open | |
03_abstract.pdf | 50.51 kB | Adobe PDF | View/Open | |
04_acknowledgement.pdf | 26.21 kB | Adobe PDF | View/Open | |
05_contents.pdf | 84.6 kB | Adobe PDF | View/Open | |
06_list_of_abbreviations.pdf | 9.54 kB | Adobe PDF | View/Open | |
07_chapter1.pdf | 140.8 kB | Adobe PDF | View/Open | |
08_chapter2.pdf | 460.79 kB | Adobe PDF | View/Open | |
09_chapter3.pdf | 369.79 kB | Adobe PDF | View/Open | |
10_chapter4.pdf | 99.01 kB | Adobe PDF | View/Open | |
11_chapter5.pdf | 72.85 kB | Adobe PDF | View/Open | |
12_conclusion.pdf | 25.85 kB | Adobe PDF | View/Open | |
13_appendices.pdf | 106.12 kB | Adobe PDF | View/Open | |
14_references.pdf | 105.05 kB | Adobe PDF | View/Open | |
15_list_of_publications.pdf | 65.41 kB | Adobe PDF | View/Open |
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