Continuous learning automata solutions to the capacity assignment problem

作     者：Oommen, BJ Roberts, TD 

作者机构：Carleton Univ Sch Comp Sci Ottawa ON K1S 5B6 Canada 

出 版 物：《IEEE TRANSACTIONS ON COMPUTERS》 (IEEE Trans Comput)

年 卷 期：2000年第49卷第6期

页      面：608-620页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Natural Sciences and Engineering Research Council of Canada  NSERC 

主　　题：learning automata capacity assignment problem network design 

摘      要：The Capacity Assignment (CA) problem focuses on finding the best possible set of capacities for the links that satisfies the traffic requirements in a prioritized network while minimizing the cost. Most approaches consider a single class of packets flowing through the network, but. in reality, different classes of packets with different packet lengths and priorities are transmitted over the networks. In this paper, we assume that the traffic consists of different classes of packets with different average packet lengths and priorities. We shall look at three different solutions to this problem. Marayuma and Tang [9] proposed a single algorithm composed of several elementary heuristic procedures. Levi and Ersoy [8] introduced a simulated annealing approach that produced substantially better results. In this paper, we introduce a new method which uses continuous learning automata to solve the problem. Our new schemes produce superior results when compared with either of the previous solutions and is, to our knowledge, currently the best known solution.