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Conference Paper: Chemical Reaction Optimization for population transition in peer-to-peer live streaming

TitleChemical Reaction Optimization for population transition in peer-to-peer live streaming
Authors
Lam, AYSXu, JLi, VOK
KeywordsLive streaming
Metaheuristic
Open queueing networks
Optimization problems
Peer to peer
Issue Date2010
PublisherIEEE.
Citation
The IEEE Congress on Evolutionary Computation (CEC), Barcelona, Spain, 18-23 July 2010. In Proceedings of the IEEE CEC, 2010, p. 1-8 How to Cite?
DOI: http://dx.doi.org/10.1109/CEC.2010.5585933
AbstractPeer-to-peer (P2P) live streaming applications are very popular in recent years and a Markov open queueing network model was developed to study the population dynamics in P2P live streaming. Based on the model, we deduce an optimization problem, called population transition problem, with the objective of maximizing the probability of universal streaming by manipulating population transition probability matrix. We employ a chemical reaction-inspired metaheuristic, Chemical Reaction Optimization (CRO), to solve the problem. Simulation results show that CRO outperforms many commonly used strategies for controlling population transition in many practical P2P live streaming systems. This work also shows that CRO also demonstrates the usability of CRO to solve optimization problems. © 2010 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/142827
ISBN
978-1-4244-8126-2
References
References in Scopus

 

DC FieldValueLanguage
dc.contributor.authorLam, AYSen_HK
dc.contributor.authorXu, Jen_HK
dc.contributor.authorLi, VOKen_HK
dc.date.accessioned2011-10-28T02:56:11Z-
dc.date.available2011-10-28T02:56:11Z-
dc.date.issued2010en_HK
dc.identifier.citationThe IEEE Congress on Evolutionary Computation (CEC), Barcelona, Spain, 18-23 July 2010. In Proceedings of the IEEE CEC, 2010, p. 1-8en_HK
dc.identifier.isbn978-1-4244-8126-2-
dc.identifier.urihttp://hdl.handle.net/10722/142827-
dc.description.abstractPeer-to-peer (P2P) live streaming applications are very popular in recent years and a Markov open queueing network model was developed to study the population dynamics in P2P live streaming. Based on the model, we deduce an optimization problem, called population transition problem, with the objective of maximizing the probability of universal streaming by manipulating population transition probability matrix. We employ a chemical reaction-inspired metaheuristic, Chemical Reaction Optimization (CRO), to solve the problem. Simulation results show that CRO outperforms many commonly used strategies for controlling population transition in many practical P2P live streaming systems. This work also shows that CRO also demonstrates the usability of CRO to solve optimization problems. © 2010 IEEE.en_HK
dc.languageengen_US
dc.publisherIEEE.-
dc.relation.ispartofProceedings of the IEEE Congress on Evolutionary Computation, CEC 2010en_HK
dc.rights©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.subjectLive streaming-
dc.subjectMetaheuristic-
dc.subjectOpen queueing networks-
dc.subjectOptimization problems-
dc.subjectPeer to peer-
dc.titleChemical Reaction Optimization for population transition in peer-to-peer live streamingen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=978-1-4244-8126-2&volume=&spage=&epage=&date=2010&atitle=Chemical+Reaction+Optimization+for+population+transition+in+peer-to-peer+live+streaming-
dc.identifier.emailLi, VOK:vli@eee.hku.hken_HK
dc.identifier.authorityLi, VOK=rp00150en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/CEC.2010.5585933en_HK
dc.identifier.scopuseid_2-s2.0-79959444719en_HK
dc.identifier.hkuros196918en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79959444719&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage1-
dc.identifier.epage8-
dc.description.otherThe IEEE Congress on Evolutionary Computation (CEC), Barcelona, Spain, 18-23 July 2010. In Proceedings of the IEEE CEC, 2010, p. 1-8-
dc.identifier.scopusauthoridLam, AYS=35322184700en_HK
dc.identifier.scopusauthoridXu, J=26668149800en_HK
dc.identifier.scopusauthoridLi, VOK=7202621685en_HK

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