An adaptive-evolution-based quantum-inspired evolutionary algorithm for QoS multicasting in IP/DWDM networks

Authors:
Huanlai Xing;Yuefeng Ji;Lin Bai;Xin Liu;Zhijian Qu;Xiaoling Wang
Affiliations:
Key Laboratory of Optical Communication & Lightwave Technologies, Ministry of Education, Beijing University of Posts & Telecommunications, Beijing 100876, PR China;Key Laboratory of Optical Communication & Lightwave Technologies, Ministry of Education, Beijing University of Posts & Telecommunications, Beijing 100876, PR China;Key Laboratory of Optical Communication & Lightwave Technologies, Ministry of Education, Beijing University of Posts & Telecommunications, Beijing 100876, PR China;Key Laboratory of Optical Communication & Lightwave Technologies, Ministry of Education, Beijing University of Posts & Telecommunications, Beijing 100876, PR China;Key Laboratory of Optical Communication & Lightwave Technologies, Ministry of Education, Beijing University of Posts & Telecommunications, Beijing 100876, PR China;Key Laboratory of Optical Communication & Lightwave Technologies, Ministry of Education, Beijing University of Posts & Telecommunications, Beijing 100876, PR China
Venue:
Computer Communications
Year:
2009

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Abstract

This paper investigates least-cost QoS multicast routing problem in IP/DWDM optical networks, and proposes an improved evolutionary algorithm (AEQEA). Based on quantum-inspired evolutionary algorithm (QEA) with quantum rotation gate strategy, AEQEA introduces adaptive evolution mechanism (AEM), which allows each chromosome in a population to update itself to a fitter position according to its own situation. In term of this mechanism, AEQEA can significantly improve its capability of exploration and exploitation, since every chromosome is able to be allocated with suitable evolutionary parameters before each update. A repair method is applied to eliminate illegal graphs as many as possible hence more excellent solutions will appear in each evolutionary generation. Simulations are carried out over a number of network topologies. And the results show that, for the QoS multicasting problem, AEQEA outperforms other existing heuristic algorithms and is characterized by robustness, high success ratio, fast convergence and excellent capability on global searching.