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Investigation of fitness function weight-coefficients for optimization in WMN-PSO simulation system

dc.contributor.authorSakamoto, Shinji
dc.contributor.authorOda, Tetsuya
dc.contributor.authorIkeda, Makoto
dc.contributor.authorBarolli, Leonard
dc.contributor.authorXhafa Xhafa, Fatos
dc.contributor.authorWoungang, Isaac
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2017-01-10T14:27:05Z
dc.date.available2017-01-10T14:27:05Z
dc.date.issued2016
dc.identifier.citationSakamoto, S., Oda, T., Ikeda, M., Barolli, L., Xhafa, F., Woungang, I. Investigation of fitness function weight-coefficients for optimization in WMN-PSO simulation system. A: International Conference on Complex, Intelligent, and Software Intensive Systems. "2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems, CISIS 2016, Fukuoka Institute of Technology (FIT), Fukuoka, Japan 6-8 July 2016: proceedings". Fukuoka: Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 224-229.
dc.identifier.isbn978-1-5090-0987-9
dc.identifier.urihttp://hdl.handle.net/2117/98970
dc.description(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
dc.description.abstractWith the fast development of wireless technologies, Wireless Mesh Networks (WMNs) are becoming an important networking infrastructure due to their low cost and increased high speed wireless Internet connectivity. In our previous work, we implemented a simulation system based on Particle Swam Optimization for solving node placement problem in wireless mesh networks, called WMN-PSO. In this paper, we use Size of Giant Component (SGC) and Number of Covered Mesh Clients (NCMC) as metrics for optimization. Then, we analyze effects of weight-coefficients for SGC and NCMC. From the simulation results, we found that the best values of the weight-coefficients for SGC and NCMC are 0.7 and 0.3, respectively.
dc.format.extent6 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
dc.subjectÀrees temàtiques de la UPC::Informàtica
dc.subject.lcshWireless communication systems
dc.subject.lcshMathematical optimization
dc.subject.otherReplacement method
dc.subject.otherWireless Mesh Networks
dc.subject.otherParticle swarm optimization
dc.subject.otherNode placement
dc.subject.otherSGC
dc.subject.otherNCMC
dc.titleInvestigation of fitness function weight-coefficients for optimization in WMN-PSO simulation system
dc.typeConference report
dc.subject.lemacComunicació sense fil, Sistemes de
dc.subject.lemacOptimització matemàtica
dc.identifier.doi10.1109/CISIS.2016.55
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://ieeexplore.ieee.org/document/7791888/
dc.rights.accessOpen Access
local.identifier.drac18734799
dc.description.versionPostprint (author's final draft)
local.citation.authorSakamoto, S.; Oda, T.; Ikeda, M.; Barolli, L.; Xhafa, F.; Woungang, I.
local.citation.contributorInternational Conference on Complex, Intelligent, and Software Intensive Systems
local.citation.pubplaceFukuoka
local.citation.publicationName2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems, CISIS 2016, Fukuoka Institute of Technology (FIT), Fukuoka, Japan 6-8 July 2016: proceedings
local.citation.startingPage224
local.citation.endingPage229


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