Learning algorithms for quality of service multicast routing

作     者：Reeve, J Mars, P Hodgkinson, T 

作者机构：Univ Durham Sch Engn Ctr Telecommun Networks Durham DH1 3LE England BT Labs Ipswich IP5 7RE Suffolk England 

出 版 物：《ELECTRONICS LETTERS》 (电子学快报)

年 卷 期：1998年第34卷第12期

页      面：1195-1197页

核心收录：

学科分类：0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

主　　题：dynamic membership telecommunication network routing tree shortest path telecommunication services quality of service multicast routing stochastic automata load balancing trees (mathematics) stochastic learning automata local connectivity telecommunication channels learning algorithm learning automata blocking probability 

摘      要：Stochastic learning automata are used to grow quality of service bounded multicast trees in a dynamic membership environment. It is found that learning automata, which use minimal state information and require only local connectivity knowledge, provide superior results to alternative shortest path approaches by learning to minimise the number of blocked connection attempts via load balancing.