한국통신학회논문지 (The Journal of Korean Institute of Communications and Information Sciences)

  • 제41권7호
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  • Pages.754-764
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  • 2016
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  • 1226-4717(pISSN)
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  • 2287-3880(eISSN)
한국통신학회 (The Korean Institute of Commucations and Information Sciences)
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Small-World 망과 Scale-Free 망을 위한 일반적인 망 생성 방법

Generalized Network Generation Method for Small-World Network and Scale-Free Network

  • Lee, Kang-won (Seoul National University of Science & Technology) ;
  • Lee, Jae-hoon (Seoul National University of Science & Technology) ;
  • Choe, Hye-zin (Seoul National University of Science & Technology)
  • 투고 : 2016.04.19
  • 심사 : 2016.07.26
  • 발행 : 2016.07.31
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초록

최근 들어 다양한 SNS(Social Network Service)에 대한 이해와 분석을 위해 가장 중요한 두 종류의 망인 small-world와 scale-free망에 대한 많은 연구가 수행되고 있다. 본 연구에서는 두 개의 입력 파라미터를 적절히 조정함으로서 small-world 망, scale-free 망 혹은 두 개의 성질을 동시에 모두 갖는 망을 생성 할 수 있는 보다 일반화된 망 생성 방법을 제안하였다. 두개의 입력 파라미터중 하나는 small-world 성질을 나태내주는 파라미터고 다른 하나는 scale-free와 small-world 성질 모두를 나타내주는 파라미터다. Small-world와 scale-free를 나타내주는 망의 성질로 군집계수, 평균 최단거리 그리고 power-law 상수를 이용하였다. 본 연구에서 제안한 방법을 사용하면 small-world 망과 scale-free 망의 성질과 관계에 대한 보다 명확한 이해를 할 수 있다. 다양한 여러 예제들을 통하여 두 개의 입력 파라미터들이 군집계수, 평균 최단거리 그리고 power-law 상수에 미치는 영향을 검증하였다. 이를 통해 어떠한 입력 파라미터들의 조합이 small-world 망, scale-free 망 혹은 두 개의 성질을 모두 갖는 망을 생성 할 수 있는지를 조사하였다.

To understand and analyze SNS(Social Network Service) two important classes of networks, small-world and scale-free networks have gained a lot of research interests. In this study, a generalized network generation method is developed, which can produce small-world network, scale-free network, or network with the properties of both small-world and scale-free by controlling two input parameters. By tuning one parameter we can represent the small-world property and by tuning the other one we can represent both scale-free and small-world properties. For the network measures to represent small-world and scale-free properties clustering coefficient, average shortest path distance and power-law property are used. Using the model proposed in this study we can have more clear understanding about relationships between small-world network and scale-free network. Using numerical examples we have verified the effects of two parameters on clustering coefficient, average shortest path distance and power-law property. Through this investigation it can be shown that small-world network, scale-free network or both can be generated by tuning two input parameters properly.

키워드

참고문헌

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