Please use this identifier to cite or link to this item:
https://scholarbank.nus.edu.sg/handle/10635/14239
DC Field | Value | |
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dc.title | A new numerical performance analysis method of leaky bucket policing algorithm over heavy-tailed on/off internet traffic | |
dc.contributor.author | LUO HAIHONG | |
dc.date.accessioned | 2010-04-08T10:41:11Z | |
dc.date.available | 2010-04-08T10:41:11Z | |
dc.date.issued | 2004-09-18 | |
dc.identifier.citation | LUO HAIHONG (2004-09-18). A new numerical performance analysis method of leaky bucket policing algorithm over heavy-tailed on/off internet traffic. ScholarBank@NUS Repository. | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/14239 | |
dc.description.abstract | Although many facets of Leaky Bucket (LB) Policing have been studied in the internet Quality of Service (QoS) research community, an effective method is yet to be found to estimate actual loss performance parameters introduced by LB when it is regulating internet flow of empirical models with heavy-tailed distributions. Our analysis of a publicly available internet traffic trace data reveals that the ON/OFF periods of downlink data follow Weibull distributions. Our study provides a numerical method to analyze the LB Policing performance in a Weibull ON/OFF traffic model scenario based on this empirical traffic trace study. Since properties of distributions and the system model equation found in this study can be found in a variety of distributions, not just in Weibull distribution, therefore, our method is essentially applicable as a more general solution in a scenario to any scenario sharing the same properties. | |
dc.language.iso | en | |
dc.subject | Leaky Bucket, heavy-tailed, internet traffic, loss performance, numerical | |
dc.type | Thesis | |
dc.contributor.department | ELECTRICAL & COMPUTER ENGINEERING | |
dc.contributor.supervisor | WONG TUNG CHONG | |
dc.description.degree | Master's | |
dc.description.degreeconferred | MASTER OF ENGINEERING | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Master's Theses (Open) |
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File | Description | Size | Format | Access Settings | Version | |
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Thesis.pdf | 1.52 MB | Adobe PDF | OPEN | None | View/Download |
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