Quality of Service Metrics using Generalized Pareto Distribution
Computer networks are becoming an important aspect of our life. More users are competing for limited resources; degradation in the quality of service is thus unavoidable. Proper modeling of bursts and serious deterioration is important. We model network traffic bursts using generalized Pareto distri...
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my.utp.eprints.45472014-03-31T17:13:06Z Quality of Service Metrics using Generalized Pareto Distribution Youssouf Dahab, Abdoul Mahmoud Md Said, Abas Hasbullah, Halabi T Technology (General) Computer networks are becoming an important aspect of our life. More users are competing for limited resources; degradation in the quality of service is thus unavoidable. Proper modeling of bursts and serious deterioration is important. We model network traffic bursts using generalized Pareto distribution. This method is based on the extreme value theory. We simulated external and collected internal network traffic traces. We found that GPD models these two types of traffic correctly and with clear differences between them. New measures and metrics can be defined out of the GPD modeling to be included in the service level agreement between provider and users. This will have the impact of enhancing in the expected quality of service, especially for mission critical applications. 2010-06 Conference or Workshop Item PeerReviewed text/html http://eprints.utp.edu.my/4547/1/abs_all.jsp%3Farnumber%3D5561554%26tag%3D1 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5561554 Youssouf Dahab, Abdoul Mahmoud and Md Said, Abas and Hasbullah, Halabi (2010) Quality of Service Metrics using Generalized Pareto Distribution. In: 4th International Symposium on Information Technology 2010 (ITSim'10), 15-17 June 2010, KLCC, Kuala Lumpur. http://eprints.utp.edu.my/4547/ |
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T Technology (General) Youssouf Dahab, Abdoul Mahmoud Md Said, Abas Hasbullah, Halabi Quality of Service Metrics using Generalized Pareto Distribution |
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Computer networks are becoming an important aspect of our life. More users are competing for limited resources; degradation in the quality of service is thus unavoidable. Proper modeling of bursts and serious deterioration is important. We model network traffic bursts using generalized Pareto distribution. This method is based on the extreme value theory. We simulated external and collected internal network traffic traces. We found that GPD models these two types of traffic correctly and with clear differences between them. New measures and metrics can be defined out of the GPD modeling to be included in the service level agreement between provider and users. This will have the impact of enhancing in the expected quality of service, especially for mission critical applications. |
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Conference or Workshop Item |
author |
Youssouf Dahab, Abdoul Mahmoud Md Said, Abas Hasbullah, Halabi |
author_facet |
Youssouf Dahab, Abdoul Mahmoud Md Said, Abas Hasbullah, Halabi |
author_sort |
Youssouf Dahab, Abdoul Mahmoud |
title |
Quality of Service Metrics using Generalized Pareto Distribution
|
title_short |
Quality of Service Metrics using Generalized Pareto Distribution
|
title_full |
Quality of Service Metrics using Generalized Pareto Distribution
|
title_fullStr |
Quality of Service Metrics using Generalized Pareto Distribution
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Quality of Service Metrics using Generalized Pareto Distribution
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title_sort |
quality of service metrics using generalized pareto distribution |
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2010 |
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http://eprints.utp.edu.my/4547/1/abs_all.jsp%3Farnumber%3D5561554%26tag%3D1 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5561554 http://eprints.utp.edu.my/4547/ |
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13.211869 |