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dc.contributor.authorCheng, Huien
dc.contributor.authorWang, Xingweien
dc.contributor.authorYang, Shengxiangen
dc.contributor.authorHuang, Minen
dc.date.accessioned2013-05-17T10:27:58Z
dc.date.available2013-05-17T10:27:58Z
dc.date.issued2009
dc.identifier.citationCheng, H. et al. (2009) A multipopulation parallel genetic simulated annealing-based QoS routing and wavelength assignment integration algorithm for multicast in optical networks. Applied Soft Computing, 9(2), March 2009, pp. 677-684.en
dc.identifier.issn1568-4946
dc.identifier.urihttp://hdl.handle.net/2086/8591
dc.description.abstractIn this paper, we propose an integrated Quality of Service (QoS) routing algorithm for optical networks. Given a QoS multicast request and the delay interval specified by users, the proposed algorithm can find a flexible-QoS-based cost suboptimal routing tree. The algorithm first constructs the multicast tree based on the multipopulation parallel genetic simulated annealing algorithm, and then assigns wavelengths to the tree based on the wavelength graph. In the algorithm, routing and wavelength assignment are integrated into a single process. For routing, the objective is to find a cost suboptimal multicast tree. For wavelength assignment, the objective is to minimize the delay of the multicast tree, which is achieved by minimizing the number of wavelength conversion. Thus both the cost of multicast tree and the user QoS satisfaction degree can approach the optimal. Our algorithm also considers load balance. Simulation results show that the proposed algorithm is feasible and effective. We also discuss the practical realization mechanisms of the algorithm.en
dc.language.isoenen
dc.publisherElsevier.en
dc.subjectOptical networken
dc.subjectMulticasten
dc.subjectWavelength assignmenten
dc.subjectMultipopulation genetic simulated annealing algorithmen
dc.titleA multipopulation parallel genetic simulated annealing-based QoS routing and wavelength assignment integration algorithm for multicast in optical networks.en
dc.typeArticleen
dc.identifier.doihttp://dx.doi.org/10.1016/j.asoc.2008.09.008
dc.researchgroupCentre for Computational Intelligenceen
dc.peerreviewedYesen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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