Analysis On QOS Parameters To Predict Http Response

Current web service standards lack the best framework to predict the best possible QoS parameters to predict the best delivery service to guarantee packets being delivered to the destination and the order of the arriving packets through the HTTP. It is because of the proliferation of the same web se...

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Main Author: A.Rahman, Khairulnizam
Format: Thesis
Language:English
English
Published: 2017
Subjects:
Online Access:http://eprints.utem.edu.my/id/eprint/20727/
http://libraryopac.utem.edu.my/webopac20/Record/0000106654
Abstract Abstract here
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author A.Rahman, Khairulnizam
author_facet A.Rahman, Khairulnizam
author_sort A.Rahman, Khairulnizam
description Current web service standards lack the best framework to predict the best possible QoS parameters to predict the best delivery service to guarantee packets being delivered to the destination and the order of the arriving packets through the HTTP. It is because of the proliferation of the same web service functionality, reliability and reputation on published information. However, it is not an easy task to propose the required QoS to users because of the dynamic nature of web services and web service features, uncertain with differences applications and web services of different QoS requirements. Therefore, the real live world web service label data uses to evaluate the focus parameters using classification machine learning algorithms to process the data. The specific objective of this research was to predict simple method of measuring response time and encounter performance bottlenecks due to the limitations of the underlying messaging and transport protocols for the web services. By improving QoS services will bring advantages and competitiveness of network service providers increase bandwidth and better speed performances desire with significant parameters for users. The findings of this research have a number of important implications for future practice.
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spelling utem-207272022-02-07T16:05:59Z http://eprints.utem.edu.my/id/eprint/20727/ Analysis On QOS Parameters To Predict Http Response A.Rahman, Khairulnizam T Technology (General) TK Electrical engineering. Electronics Nuclear engineering Current web service standards lack the best framework to predict the best possible QoS parameters to predict the best delivery service to guarantee packets being delivered to the destination and the order of the arriving packets through the HTTP. It is because of the proliferation of the same web service functionality, reliability and reputation on published information. However, it is not an easy task to propose the required QoS to users because of the dynamic nature of web services and web service features, uncertain with differences applications and web services of different QoS requirements. Therefore, the real live world web service label data uses to evaluate the focus parameters using classification machine learning algorithms to process the data. The specific objective of this research was to predict simple method of measuring response time and encounter performance bottlenecks due to the limitations of the underlying messaging and transport protocols for the web services. By improving QoS services will bring advantages and competitiveness of network service providers increase bandwidth and better speed performances desire with significant parameters for users. The findings of this research have a number of important implications for future practice. 2017 Thesis NonPeerReviewed text en http://eprints.utem.edu.my/id/eprint/20727/1/Analysis%20On%20QOS%20Parameters%20To%20Predict%20Http%20Response%20-%20Khairulnizam%20A.Rahman%20-%2024%20Pages.pdf text en http://eprints.utem.edu.my/id/eprint/20727/2/Analysis%20On%20QOS%20Parameters%20To%20Predict%20Http%20Response.pdf A.Rahman, Khairulnizam (2017) Analysis On QOS Parameters To Predict Http Response. Masters thesis, Universiti Teknikal Malaysia Melaka. http://libraryopac.utem.edu.my/webopac20/Record/0000106654
spellingShingle T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
A.Rahman, Khairulnizam
Analysis On QOS Parameters To Predict Http Response
thesis_level Master
title Analysis On QOS Parameters To Predict Http Response
title_full Analysis On QOS Parameters To Predict Http Response
title_fullStr Analysis On QOS Parameters To Predict Http Response
title_full_unstemmed Analysis On QOS Parameters To Predict Http Response
title_short Analysis On QOS Parameters To Predict Http Response
title_sort analysis on qos parameters to predict http response
topic T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
url http://eprints.utem.edu.my/id/eprint/20727/
http://libraryopac.utem.edu.my/webopac20/Record/0000106654
work_keys_str_mv AT arahmankhairulnizam analysisonqosparameterstopredicthttpresponse