Multiobjective QoS multicast routing with genetic optimization algorithm

被引:0
|
作者
Gui Chao [1 ]
Sun BaoLin [1 ]
Wang Hong [1 ]
机构
[1] Hubei Univ Econ, Coll Comp Sci & Technol, Wuhan 430205, Hubei Province, Peoples R China
来源
ADVANCED COMPUTER TECHNOLOGY, NEW EDUCATION, PROCEEDINGS | 2007年
关键词
QoS; multicast routing; genetic algorithm; network with uncertain parameters;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the rapid development of Internet, mobile networks and high-performance networking technology, multicast mechanism supports effective group communication and quality of service (QoS) guarantee ensures transmission reliability. This is also a challenging and hard problem for the next generation Internet and high-performance networks. It attracts the interests of many people. This paper describes a network model for researching the QoS multicast routing problem and we propose a new multicast tree selection algorithm based on genetic algorithms to simultaneously optimize multiple QoS parameters. The paper mainly presents an efficient Multiobjective QoS Multicast routing with Genetic optimization Algorithm (MQMGA). Simulation results demonstrate that the algorithm is capable of discovering a set of QoS-based near optimized, non-dominated multicast routes within a few iterations, even for the dynamic networks environment with uncertain parameters. From this set of non-dominated solutions the end user can choose his/her favorite solution depending on his/her hard and soft QoS requirements. MQMGA is an available approach to QoS multicast routing decision.
引用
收藏
页码:207 / 212
页数:6
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