Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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Efficient Construction of Large Scale Grade of Services Steiner Tree Using Space Locality and Polynomial-Time Approximation Scheme

공간 지역성과 PTAS를 활용한 대형 GOSST의 효과적 구성

  • Kim, In-Bum (Dept. of Internet Information, Kimpo College)
  • Received : 2011.07.28
  • Accepted : 2011.08.30
  • Published : 2011.11.30
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Abstract

As the problem of GOSST building belongs to NP compete domain, heuristics for the problem ask for immense amount execution time and computations in large scale inputs. In this paper, we propose an efficient mechanism for GOSST construction using space locality PTAS. For 40,000 input nodes with maximum weight 100, the proposed space locality PTAS GOSST with 16 unit areas can reduce about 4.00% of connection cost and 89.26% of execution time less than weighted minimum spanning tree method. Though the proposed method increases 0.03% of connection cost more, but cuts down 96.39% of execution time less than approximate GOSST method (SGOSST) without PTAS. Therefore the proposed space locality PTAS GOSST mechanism can work moderately well to many useful applications where a greate number of weighted inputs should be connected in short time with approximate minimum connection cost.

GOSST의 생성은 NP-Complete 영역에 속하므로, 이 문제를 위한 휴리스틱들은, 다수의 입력 노드에 대해서 많은 시간과 계산을 요구한다. 본 논문에서는 가중치를 가지는 많은 입력 노드에 대해, 공간 지역성을 반영한 PTAS를 적용하여 GOSST를 효과적으로 구성하는 방법을 제안한다. 최대 가중치가 100인 40,000개의 입력 노드에 대하여 16개의 단위 영역으로 설계된 공간 지역성 PTAS GOSST는, 가중치 최소 신장 트리를 이용한 방법과 비교하여 연결비용은 약 4.00%, 실행시간은 89.26%를 절감할 수 있었으며, PTAS를 이용하지 않은 근사 GOSST 방법(SGOSST)에 비해서 연결비용은 0.03% 증가했으나, 실행시간은 96.39% 감소시켰다. 따라서 제안된 공간 지역성 PTAS GOSST 방법은 수많은 가중치 입력 노드들을 최소비용으로 신속히 연결하려는 다양한 응용에 잘 적용될 수 있을 것이다.

Keywords

References

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