Fuzzy simulated evolution algorithm for topology design of campusnetworks
The topology design of campus networks is a hard constrained combinatorial optimization problem. It consists of deciding the number, type, and location of the active network elements (nodes) and links. This choice is dictated by physical and technological constraints and must optimize several object...
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| مؤلفون آخرون: | , , |
| التنسيق: | article |
| منشور في: |
2000
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://eprints.kfupm.edu.sa/id/eprint/14850/1/14850_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14850/2/14850_2.doc |
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| _version_ | 1864513384521662464 |
|---|---|
| author | Youssef, H. |
| author2 | Sait, Sadiq M. Khan, S.A. unknown |
| author2_role | author author author |
| author_facet | Youssef, H. Sait, Sadiq M. Khan, S.A. unknown |
| author_role | author |
| dc.creator.none.fl_str_mv | Youssef, H. Sait, Sadiq M. Khan, S.A. unknown |
| dc.date.none.fl_str_mv | 2000 2020 |
| dc.format.none.fl_str_mv | application/pdf application/msword |
| dc.identifier.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/14850/1/14850_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14850/2/14850_2.doc (2000) Fuzzy simulated evolution algorithm for topology design of campusnetworks. Evolutionary Computation, 2000. Proceedings of the 2000 Congress on, 1. |
| dc.language.none.fl_str_mv | en en |
| dc.publisher.none.fl_str_mv | IEEE |
| dc.relation.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/14850/ |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Computer |
| dc.title.none.fl_str_mv | Fuzzy simulated evolution algorithm for topology design of campusnetworks |
| dc.type.none.fl_str_mv | Article PeerReviewed info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | The topology design of campus networks is a hard constrained combinatorial optimization problem. It consists of deciding the number, type, and location of the active network elements (nodes) and links. This choice is dictated by physical and technological constraints and must optimize several objectives. Example of objectives are monetary cost, network delay, and hop count between communicating pairs. Furthermore, due to the nondeterministic nature of network traffic and other design parameters, the objective criteria are imprecise. Fuzzy logic provides a suitable mathematical framework in such a situation. We present an approach based on the simulated evolution algorithm for the design of campus network topology. The two main phases of the algorithm, namely, evaluation and allocation, have been fuzzified. To diversify the search, we have also incorporated tabu search-based characteristics in the allocation phase of the SE algorithm. This approach is then compared with the simulated annealing algorithm, which is another well-known heuristic. Results show that on all test cases the simulated evolution algorithm exhibits more intelligent search of the solution subspace and was able to find better solutions than simulated annealing |
| eu_rights_str_mv | openAccess |
| format | article |
| id | KFUPM_010506731550e270e422404d64f7b66b |
| identifier_str_mv | (2000) Fuzzy simulated evolution algorithm for topology design of campusnetworks. Evolutionary Computation, 2000. Proceedings of the 2000 Congress on, 1. |
| language_invalid_str_mv | en |
| network_acronym_str | KFUPM |
| network_name_str | King Fahd University of Petroleum and Minerals |
| oai_identifier_str | oai::14850 |
| publishDate | 2000 |
| publisher.none.fl_str_mv | IEEE |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Fuzzy simulated evolution algorithm for topology design of campusnetworksYoussef, H.Sait, Sadiq M.Khan, S.A.unknownComputerThe topology design of campus networks is a hard constrained combinatorial optimization problem. It consists of deciding the number, type, and location of the active network elements (nodes) and links. This choice is dictated by physical and technological constraints and must optimize several objectives. Example of objectives are monetary cost, network delay, and hop count between communicating pairs. Furthermore, due to the nondeterministic nature of network traffic and other design parameters, the objective criteria are imprecise. Fuzzy logic provides a suitable mathematical framework in such a situation. We present an approach based on the simulated evolution algorithm for the design of campus network topology. The two main phases of the algorithm, namely, evaluation and allocation, have been fuzzified. To diversify the search, we have also incorporated tabu search-based characteristics in the allocation phase of the SE algorithm. This approach is then compared with the simulated annealing algorithm, which is another well-known heuristic. Results show that on all test cases the simulated evolution algorithm exhibits more intelligent search of the solution subspace and was able to find better solutions than simulated annealingIEEE20002020ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/mswordhttps://eprints.kfupm.edu.sa/id/eprint/14850/1/14850_1.pdfhttps://eprints.kfupm.edu.sa/id/eprint/14850/2/14850_2.doc (2000) Fuzzy simulated evolution algorithm for topology design of campusnetworks. Evolutionary Computation, 2000. Proceedings of the 2000 Congress on, 1. enenhttps://eprints.kfupm.edu.sa/id/eprint/14850/info:eu-repo/semantics/openAccessoai::148502019-11-01T14:07:44Z |
| spellingShingle | Fuzzy simulated evolution algorithm for topology design of campusnetworks Youssef, H. Computer |
| status_str | publishedVersion |
| title | Fuzzy simulated evolution algorithm for topology design of campusnetworks |
| title_full | Fuzzy simulated evolution algorithm for topology design of campusnetworks |
| title_fullStr | Fuzzy simulated evolution algorithm for topology design of campusnetworks |
| title_full_unstemmed | Fuzzy simulated evolution algorithm for topology design of campusnetworks |
| title_short | Fuzzy simulated evolution algorithm for topology design of campusnetworks |
| title_sort | Fuzzy simulated evolution algorithm for topology design of campusnetworks |
| topic | Computer |
| url | https://eprints.kfupm.edu.sa/id/eprint/14850/1/14850_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14850/2/14850_2.doc |