Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/421153
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | Computer Science and Engineering | |
dc.date.accessioned | 2022-11-29T12:56:06Z | - |
dc.date.available | 2022-11-29T12:56:06Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/421153 | - |
dc.description.abstract | With the ever increasing demand for Internet services the knowledge of Internet traffic data is very essential for addressing various network wide applications within an Internet Protocol IP backbone network However the high dimensional multivariate structure of Internet traffic data proves to be a major hurdle in addressing these applications Decomposition techniques based on Principal Component Analysis PCA which provides a low dimensional representation of Internet traffic data have... | |
dc.format.extent | Not Available | |
dc.language | English | |
dc.relation | Not Available | |
dc.rights | university | |
dc.title | Estimation reconstruction and analysis of internet traffic data using decomposition techniques | |
dc.title.alternative | Not available | |
dc.creator.researcher | Kumar, Awnish | |
dc.subject.keyword | Computer Science | |
dc.subject.keyword | Engineering and Technology | |
dc.subject.keyword | Telecommunications | |
dc.description.note | Not Available | |
dc.contributor.guide | Saradhi, V Vijaya and Venkatesh, T | |
dc.publisher.place | Guwahati | |
dc.publisher.university | Indian Institute of Technology Guwahati | |
dc.publisher.institution | Department of Computer Science and Engineering | |
dc.date.registered | 2011 | |
dc.date.completed | 2021 | |
dc.date.awarded | 2021 | |
dc.format.dimensions | Not Available | |
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Department of Computer Science and Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_fulltext.pdf | Attached File | 3.02 MB | Adobe PDF | View/Open |
04_abstract.pdf | 203.22 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 188.69 kB | Adobe PDF | View/Open |
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