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http://hdl.handle.net/10603/304299
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DC Field | Value | Language |
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dc.coverage.spatial | ||
dc.date.accessioned | 2020-10-27T05:48:27Z | - |
dc.date.available | 2020-10-27T05:48:27Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/304299 | - |
dc.description.abstract | The optical network has been widely preferred by the operators for its newlineenormous bandwidth, low attenuation, reliable high speed transportation and scalability. newlineThe next generation optical networking involves exploiting the artificial intelligence and newlinecognitive methods to cater the necessities of the emerging internet based services. newlineImproving the Quality of Transmission (QoT) of such services without any additional newlinecost becomes the most challenging aspect in future communication system. Some of the newlineimportant challenges lie in computing the route and wavelength of the optical paths, newlineknown as RWA (Routing and Wavelength Assignment) problem. Even if the newlinecomputational complexity of online RWA algorithm is NP Hard, the sub optimal or best newlineeffort solutions can be computed in reasonable time. newlineIn this work, the RWA problem was analyzed and the avenues to improve newlinethe QoT with the optical based enabling technologies and cognition based software newlinedefined networking paradigm were explored. Initially, the need for Path Computation newlineElement (PCE) based algorithm selection approach for the enhancement of quality of newlinetransmission was discussed. Then, the single PCE based algorithm selection method newlinewith the utilization of dynamic selection of child PCEs was proposed and validated in a newlinesingle network autonomous system newline | |
dc.format.extent | ||
dc.language | English | |
dc.relation | ||
dc.rights | university | |
dc.title | Algorithm Selection Approach to Design Logical Topology in Next Generation Optical Networks | |
dc.title.alternative | ||
dc.creator.researcher | Selvaraj.P | |
dc.subject.keyword | Computer Science | |
dc.subject.keyword | Computer Science Artificial Intelligence | |
dc.subject.keyword | Engineering and Technology | |
dc.description.note | ||
dc.contributor.guide | Prabakaran.S | |
dc.publisher.place | Kattankulathur | |
dc.publisher.university | SRM University | |
dc.publisher.institution | Department of Computer Science Engineering | |
dc.date.registered | ||
dc.date.completed | 2019 | |
dc.date.awarded | ||
dc.format.dimensions | ||
dc.format.accompanyingmaterial | DVD | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Department of Computer Science Engineering |
Files in This Item:
File | Description | Size | Format | |
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80_recommendation.pdf | Attached File | 64.57 kB | Adobe PDF | View/Open |
abstract.pdf | 22.93 kB | Adobe PDF | View/Open | |
acknowledgment.pdf | 19.63 kB | Adobe PDF | View/Open | |
chapter 1.pdf | 238.1 kB | Adobe PDF | View/Open | |
chapter 2.pdf | 83.45 kB | Adobe PDF | View/Open | |
chapter 3.pdf | 420.35 kB | Adobe PDF | View/Open | |
chapter 4.pdf | 192.63 kB | Adobe PDF | View/Open | |
chapter 5.pdf | 574.77 kB | Adobe PDF | View/Open | |
chapter 6.pdf | 25.81 kB | Adobe PDF | View/Open | |
curriculum vitae.pdf | 18.41 kB | Adobe PDF | View/Open | |
declaration.pdf | 23.39 kB | Adobe PDF | View/Open | |
list of publications.pdf | 20.36 kB | Adobe PDF | View/Open | |
preliminary pages.pdf | 47.58 kB | Adobe PDF | View/Open | |
references.pdf | 61.74 kB | Adobe PDF | View/Open | |
title.pdf | 50.22 kB | Adobe PDF | View/Open |
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