A New Heuristic Method Improvement for Ring Topology Optimization: Proposal Algorithm Syamsul Qamar, Sigit Haryadi, and Nana R. Syambas School of Electrical Engineering and Informatics, Institut Teknologi Bandung (ITB) Bandung 40132, Indonesia Email: syamsul27@students.itb.ac.id; sigitharyadi59@gmail.com; nana@stei.itb.ac.id Abstract —The issue of optimization is very important in designing computer network. Designing a ring topology is about connecting a set of point-shaped nodes which are each connected to two other points, thus forming a circular path forming a ring. This idea tries to formulate an algorithm to optimize the ring topology by using an approach that is on the Traveling Salesman Problem (TSP). There are two variables considered in TSP. Both are the strategy to find the node configuration which has minimum cost as well as the most minimum time consumption for its execution. To measure the extent to which the proposed algorithm can perform optimization, then made a comparison with some existing algorithms such as Brute force, Ant colony, and Bambang. Brute Force has the ability to find the absolute minimum node configuration cost but in terms of time to complete it increases exponentially. While it does not provide the minimum cost, the Ant Colony Optimization algorithm (ACO) has the minimal advantage needed to find the minimum node configuration. This paper proposes a heuristic algorithm to find the sub-minimum node configuration. The proposed algorithm has the shortest time of fewer than 50 seconds to 50 nodes, compared to other algorithms while the cost of node configuration is not always lower than Ant Colony. Index Terms—TSP, heuristic, ring toplogy, network design, routing algorithm, ant colony, brute force I. INTRODUCTION Over the last few decades, we have witnessed a growth in data traffic. This growth, driven by Internet proliferation, has created an increasing demand for robust networks, with increased link and node capacity. In metropolitan networks ring network topology is the most popular topology which uses the link bandwidth efficiently and increases the capacity of the system. However, there is a need for an efficient solution for transporting and switching huge amounts of data at the boundaries of backbone networks, especially at metropolitan and local area networks [1]. Design ring topology itself can be modelled like the Traveling Salesman Problem (TSP), which is a problem of optimization to search the shortest route for peddler who wants to visit several cities [2]. The traveling salesman problem, TSP for short, has model character in Manuscript received April 16, 2018; revised September 12, 2018. This work was supported by LPDP (Lembaga Pengelola Dana Pendidikan), Menistry of Finance, Republic of Indonesia Corresponding author email: syamsul27@students.itb.ac.id doi:10.12720/jcm.13.10.607-611 many branches of Mathematics, Computer Science, and Operations Research. Heuristics, linear programming, and branch and bound, which are still the main components of today’s most successful approaches to hard combinatorial optimization problems [3]. The complexity of the TSP problem algorithm is about continuously challenging issue until today, even after 50 years of searching. This makes TSP one of the most untapped issues in many mathematical optimization problems [4]. The proposed algorithm used a purely heuristic method, which is mean using only the available information at that time to make decision to added new node. In this study, we tested the algorithm we proposed to build a ring topology by taking the problems in the TSP and compares with some popular algorithms that are often used to solve this problem among others. A. Brute Force Brute force is a straightforward approach to solve a problem based on the problem’s statement and definitions of the concepts involved. It is considered as one of the easiest approach to apply and is useful for solving small – size instances of a problem [5]. It is often easy to implement and almost certainly will find a solution. At this time, only the brute force algorithm is able to find the absolute minimum value of the TSP. Brute force algorithm is one of the easiest ways to find the shortest link, but Brute Force takes a very long time of execution. The complexity of the algorithm for TSP problems with the Brute Force algorithm is O (n!). B. Ant Colony Ant colony optimization (ACO) was one of the first techniques for approximate optimization that was introduced in the early 1990's. The inspiring source of ant colony optimization is the foraging behavior of real ant colonies [6]. The ant colony optimization (ACO) algorithm, a classical bionic algorithm for determining the optimal path, has several advantages: it is easy to integrate with other algorithms, is amenable to distributed parallel computing, includes an intelligent search, and has good global optimization and strong robustness when compared with other swarm intelligence algorithms [7]. This behavior is exploited in artificial ant colonies for the search of approximate solutions to discrete optimization problems, to continuous optimization problems, and to important problems in telecommunications, such as routing and load balancing. 607 ©2018 Journal of Communications Journal of Communications Vol. 13, No. 10, October 2018