A new heuristic method for ring topology optimization: A proposal

B. K. G. Petrus, Syamsul Qamar, Nana R. Syambas
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引用次数: 1

Abstract

Nowadays, the ring topology has become a standard in network topology design, at least at the core network. The problem in designing ring topology is how to design the connections of each node to each other with the overall cost of the ring is minimum. This problem is known as the Traveling Salesman Problem (TSP). There are two variables which need consideration in TSP, finding the nodes configuration that has minimum cost, and how long it takes to get this minimum configuration. Brute Force has the capability to find the minimum nodes configuration cost, but with every node added to the overall configuration, the time to solve it is increasing exponentially. While not giving the minimum cost, The Ant Colony Optimization (ACO) algorithm has the advantage of minimal time needed to find the sub-minimum nodes configuration. This paper proposed a new heuristic algorithm to find the sub-minimum nodes configuration. The proposed algorithm has a shorter time, in order of less than 1 second for up to 50 nodes, compared to the Ant Colony Algorithm. Although, the cost of the nodes configuration didn't always lower than the Ant Colony Algorithm.
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一种新的启发式环拓扑优化方法:建议
目前,环拓扑已经成为网络拓扑设计的标准,至少在核心网是如此。环形拓扑设计的问题是如何在环形总代价最小的情况下设计各节点之间的连接。这个问题被称为旅行推销员问题(TSP)。在TSP中有两个变量需要考虑,找到具有最小成本的节点配置,以及获得这个最小配置所需的时间。Brute Force有能力找到最小的节点配置成本,但是随着每个节点添加到总体配置中,解决它的时间呈指数增长。蚁群优化算法虽然没有给出最小的成本,但具有查找次最小节点配置所需时间最短的优点。提出了一种寻找次最小节点配置的启发式算法。与蚁群算法相比,该算法具有更短的时间,最多可处理50个节点,大约不到1秒。然而,节点配置的成本并不总是低于蚁群算法。
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