Comparison of single and multi-objective evolutionary algorithms for robust link-state routing

Bibliographic Details
Main Author: Pereira, Vítor
Publication Date: 2015
Other Authors: Sousa, Pedro, Cortez, Paulo, Rio, Miguel, Rocha, Miguel
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/1822/38300
Summary: Traffic Engineering (TE) approaches are increasingly impor- tant in network management to allow an optimized configuration and resource allocation. In link-state routing, the task of setting appropriate weights to the links is both an important and a challenging optimization task. A number of different approaches has been put forward towards this aim, including the successful use of Evolutionary Algorithms (EAs). In this context, this work addresses the evaluation of three distinct EAs, a single and two multi-objective EAs, in two tasks related to weight setting optimization towards optimal intra-domain routing, knowing the network topology and aggregated traffic demands and seeking to mini- mize network congestion. In both tasks, the optimization considers sce- narios where there is a dynamic alteration in the state of the system, in the first considering changes in the traffic demand matrices and in the latter considering the possibility of link failures. The methods will, thus, need to simultaneously optimize for both conditions, the normal and the altered one, following a preventive TE approach towards robust configurations. Since this can be formulated as a bi-objective function, the use of multi-objective EAs, such as SPEA2 and NSGA-II, came nat- urally, being those compared to a single-objective EA. The results show a remarkable behavior of NSGA-II in all proposed tasks scaling well for harder instances, and thus presenting itself as the most promising option for TE in these scenarios.
id RCAP_60d7ce7c088ca36b021334fcf8082ac1
oai_identifier_str oai:repositorium.sdum.uminho.pt:1822/38300
network_acronym_str RCAP
network_name_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository_id_str https://opendoar.ac.uk/repository/7160
spelling Comparison of single and multi-objective evolutionary algorithms for robust link-state routingMulti-objective evolutionary algorithmsTraffic EngineeringNSGASPEAintra-domain routingOSPFEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e InformáticaScience & TechnologyTraffic Engineering (TE) approaches are increasingly impor- tant in network management to allow an optimized configuration and resource allocation. In link-state routing, the task of setting appropriate weights to the links is both an important and a challenging optimization task. A number of different approaches has been put forward towards this aim, including the successful use of Evolutionary Algorithms (EAs). In this context, this work addresses the evaluation of three distinct EAs, a single and two multi-objective EAs, in two tasks related to weight setting optimization towards optimal intra-domain routing, knowing the network topology and aggregated traffic demands and seeking to mini- mize network congestion. In both tasks, the optimization considers sce- narios where there is a dynamic alteration in the state of the system, in the first considering changes in the traffic demand matrices and in the latter considering the possibility of link failures. The methods will, thus, need to simultaneously optimize for both conditions, the normal and the altered one, following a preventive TE approach towards robust configurations. Since this can be formulated as a bi-objective function, the use of multi-objective EAs, such as SPEA2 and NSGA-II, came nat- urally, being those compared to a single-objective EA. The results show a remarkable behavior of NSGA-II in all proposed tasks scaling well for harder instances, and thus presenting itself as the most promising option for TE in these scenarios.Springer VerlagUniversidade do MinhoPereira, VítorSousa, PedroCortez, PauloRio, MiguelRocha, Miguel2015-032015-03-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/38300engPereira, V., Sousa, P., Cortez, P., Rio, M., & Rocha, M. (2015) Comparison of single and multi-objective evolutionary algorithms for robust link-state routing. Vol. 9019. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 573-587).978-3-319-15891-40302-974310.1007/978-3-319-15892-1_39The original publication is available at http://link.springer.com/chapter/10.1007/978-3-319-15892-1_39info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T06:33:17Zoai:repositorium.sdum.uminho.pt:1822/38300Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T15:56:52.932226Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Comparison of single and multi-objective evolutionary algorithms for robust link-state routing
title Comparison of single and multi-objective evolutionary algorithms for robust link-state routing
spellingShingle Comparison of single and multi-objective evolutionary algorithms for robust link-state routing
Pereira, Vítor
Multi-objective evolutionary algorithms
Traffic Engineering
NSGA
SPEA
intra-domain routing
OSPF
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
Science & Technology
title_short Comparison of single and multi-objective evolutionary algorithms for robust link-state routing
title_full Comparison of single and multi-objective evolutionary algorithms for robust link-state routing
title_fullStr Comparison of single and multi-objective evolutionary algorithms for robust link-state routing
title_full_unstemmed Comparison of single and multi-objective evolutionary algorithms for robust link-state routing
title_sort Comparison of single and multi-objective evolutionary algorithms for robust link-state routing
author Pereira, Vítor
author_facet Pereira, Vítor
Sousa, Pedro
Cortez, Paulo
Rio, Miguel
Rocha, Miguel
author_role author
author2 Sousa, Pedro
Cortez, Paulo
Rio, Miguel
Rocha, Miguel
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Pereira, Vítor
Sousa, Pedro
Cortez, Paulo
Rio, Miguel
Rocha, Miguel
dc.subject.por.fl_str_mv Multi-objective evolutionary algorithms
Traffic Engineering
NSGA
SPEA
intra-domain routing
OSPF
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
Science & Technology
topic Multi-objective evolutionary algorithms
Traffic Engineering
NSGA
SPEA
intra-domain routing
OSPF
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
Science & Technology
description Traffic Engineering (TE) approaches are increasingly impor- tant in network management to allow an optimized configuration and resource allocation. In link-state routing, the task of setting appropriate weights to the links is both an important and a challenging optimization task. A number of different approaches has been put forward towards this aim, including the successful use of Evolutionary Algorithms (EAs). In this context, this work addresses the evaluation of three distinct EAs, a single and two multi-objective EAs, in two tasks related to weight setting optimization towards optimal intra-domain routing, knowing the network topology and aggregated traffic demands and seeking to mini- mize network congestion. In both tasks, the optimization considers sce- narios where there is a dynamic alteration in the state of the system, in the first considering changes in the traffic demand matrices and in the latter considering the possibility of link failures. The methods will, thus, need to simultaneously optimize for both conditions, the normal and the altered one, following a preventive TE approach towards robust configurations. Since this can be formulated as a bi-objective function, the use of multi-objective EAs, such as SPEA2 and NSGA-II, came nat- urally, being those compared to a single-objective EA. The results show a remarkable behavior of NSGA-II in all proposed tasks scaling well for harder instances, and thus presenting itself as the most promising option for TE in these scenarios.
publishDate 2015
dc.date.none.fl_str_mv 2015-03
2015-03-01T00:00:00Z
dc.type.driver.fl_str_mv conference paper
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/38300
url http://hdl.handle.net/1822/38300
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Pereira, V., Sousa, P., Cortez, P., Rio, M., & Rocha, M. (2015) Comparison of single and multi-objective evolutionary algorithms for robust link-state routing. Vol. 9019. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 573-587).
978-3-319-15891-4
0302-9743
10.1007/978-3-319-15892-1_39
The original publication is available at http://link.springer.com/chapter/10.1007/978-3-319-15892-1_39
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer Verlag
publisher.none.fl_str_mv Springer Verlag
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833595642284343296