• The KIPS Transactions:PartC
• /
• v.12C no.1 s.97
• /
• pp.77-82
• /
• 2005

Protection of user service becomes increasingly important since even very short interruption of service due to link or node failure will cause huge data loss and incur tremendous restoration cost in high speed network environment. Thus fast and efficient protection and restoration is one of the most important issues to be addressed. Protection methods have been proposed to provide efficiency and stability in optical networks. In this paper, an original network is separated into several domains using Hamiltonian cycle. and link protection is performed on the cycles of the domains. We have shown that protection path length can be decreased up to $57{\%}$ with marginal increase of backup capacity. Our proposed method can provide high-speed protection with marginal increase of protection capacity.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.5
• /
• pp.31-39
• /
• 2015

The degree-constrained minimum spanning tree (d-MST) problem is considered NP-complete for no exact solution-yielding polynomial algorithm has been proposed to. One thus has to resort to an heuristic approximate algorithm to obtain an optimal solution to this problem. This paper therefore presents a polynomial time algorithm which obtains an intial solution to the d-MST with the help of Kruskal's algorithm and performs k-opt on the initial solution obtained so as to derive the final optimal solution. When tested on 4 graphs, the algorithm has successfully obtained the optimal solutions.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.15 no.3
• /
• pp.211-218
• /
• 2015

This paper introduces a 'divide-and-conquer' algorithm to the travelling salesman problem (TSP). Top 10n are selected beforehand from a pool of n(n-1) data which are sorted in the ascending order of each vertex's distance. The proposed algorithm then firstly selects partial paths that are interconnected with the shortest distance $r_1=d\{v_i,v_j\}$ of each vertex $v_i$ and assigns them as individual regions. For $r_2$, it connects all inter-vertex edges within the region and inter-region edges are connected in accordance with the connection rule. Finally for $r_3$, it connects only inter-region edges until one whole Hamiltonian cycle is constructed. When tested on TSP-1(n=26) and TSP-2(n=42) of real cities and on a randomly constructed TSP-3(n=50) of the Euclidean plane, the algorithm has obtained optimal solutions for the first two and an improved one from that of Valenzuela and Jones for the third. In contrast to the brute-force search algorithm which runs in n!, the proposed algorithm runs at most 10n times, with the time complexity of $O(n^2)$.