Title :
A Hybrid Clustering Model for Hierarchical Overlay Topology
Author :
LianQing, Zhao ; Lu Jun
Author_Institution :
Sch. of Electr. & Electron. Eng., North China Electr. Power Univ., Beijing, China
Abstract :
To solve the hierarchical topology optimization issue in overlay network for multicast service, this paper proposed a hybrid clustering model (HCGA) combining k-means method with genetic algorithm. The hybrid model formulated the related issue as a multiple-objective optimization, and then modeled it as a weighted clustering problem. HCGA made fully use of genetic algorithm for better clustering performance. Based on the optimal parameter experiments, the experiment results illustrated, compared with k-means, that the proposed model is effective in topology routing performance with the different topology configuration.
Keywords :
genetic algorithms; multicast communication; pattern clustering; telecommunication network routing; telecommunication network topology; telecommunication services; hierarchical overlay topology; hierarchical topology optimization; hybrid clustering model; hybrid model based on genetic algorithm; k-means method; multicast service; multiple-objective optimization; overlay network; topology routing performance; weighted clustering problem; Circuit topology; Genetic algorithms; Genetic engineering; IP networks; Network topology; Power engineering and energy; Routing; Tree graphs; Unicast; Web and internet services; Genetic Algorithm; clustering; overlay network; topology optimization;
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
DOI :
10.1109/ICNC.2009.659