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네트워크 흐름의 속도에 따른 공간구조 변화

The Organization of Spatial Networks by the Velocity of Network Flows

  • 한이철 (서울대학교 대학원) ;
  • 이정재 (서울대학교 농업생명과학대학 조경.지역시스템공학부, 서울대학교 농업생명과학연구원) ;
  • 이성우 (서울대학교 농업생명과학대학 농경제사회학부, 서울대학교 농업생명과학연구원)
  • 투고 : 2010.09.30
  • 심사 : 2010.11.03
  • 발행 : 2011.01.31

초록

The nature of a network implies movement among vertices, and can be regarded as flows. Based on the flow concept which network follows the hydraulic fluid principle, we develop a spatial network model using Bernoulli equation. Then we explore the organization of spatial network and growth by the velocity of network flows. Results show that flow velocity determines network connections or influence of a vertex up to a point, and that the overall network structure is the result of pull force (pressure) and flow velocity. We demonstrate how one vertex can monopolize connections within a network.

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참고문헌

  1. Albert, R. and A. -L. Barabasi, 2000. Topology of Evolving Networks: Local Events and University. Physical Review Letters 85(24): 5234-5237. https://doi.org/10.1103/PhysRevLett.85.5234
  2. Barabási, A. -L. and R. Albert, 1999. Emergence of Scaling in Random Networks. Science 285: 509-512.
  3. Barthelemy, M. and A. Flammini, 2006. Optimal traffic networks. Journal of Statistical Mechanics: Theory and Experiment L07002.
  4. Bianconi, G. and A. -L. Barabasi, 2001a. Competition and multiscaling in evolving networks. Europhysics Letters 54: 436-442. https://doi.org/10.1209/epl/i2001-00260-6
  5. Bianconi, G. and A. -L. Barabási, 2001b. Bose-Einstein Condensation in Complex Networks. Physical Review Letters 86(24): 5632-5635. https://doi.org/10.1103/PhysRevLett.86.5632
  6. Boccaletti, S., V. Latora, Y. Moreno, M. Chavez and D. -U. Hwang. 2006. Complex networks: Structure and dynamics. Physics Reports 424: 175-308. https://doi.org/10.1016/j.physrep.2005.10.009
  7. Borgatti, S. P. and M. G. Everett, 2006. A Graphtheoretic perspective on centrality. Social Networks 28: 466-484. https://doi.org/10.1016/j.socnet.2005.11.005
  8. Borgatti, S. P., 2005. Centrality and network flow. Social Networks 27: 55-71. https://doi.org/10.1016/j.socnet.2004.11.008
  9. Freeman, L. C., S. P. Borgatti and D. R. White, 1991. Centrality in valued graphs: a measure of betweenness based on network flow. Social Networks 13: 141-154. https://doi.org/10.1016/0378-8733(91)90017-N
  10. Gastner, M. T. and M. E. J. Newman, 2006. The spatial structure of networks. The European Physical Journal B 49: 247-252. https://doi.org/10.1140/epjb/e2006-00046-8
  11. Goetz, S. J., Y. Han, J. L. Findeis and K. J. Brasier, 2010. US Commuting Networks and Economic Growth: Measurement and Implications for Spatial Policy. Growth and Change 41(2): 276-302. https://doi.org/10.1111/j.1468-2257.2010.00527.x
  12. Gonzalez, M., C. A. Hidalog and A. -L. Barabási, 2008. Understanding individual human mobility patterns. Nature 453: 779-782. https://doi.org/10.1038/nature06958
  13. Liu, F. and Q. Zhao, 2006. An efficient organization mechanism for spatial networks. Physica A 366: 608 -618.
  14. Masucci, A. P. and G. J. Rodgers, 2008. The network of commuters in London. Physica A 387: 3781-3788. https://doi.org/10.1016/j.physa.2008.02.041
  15. Newman, M. E. J., 2005. A measure of betweenness centrality based on random walks. Social Networks 27: 39-54. https://doi.org/10.1016/j.socnet.2004.11.009
  16. Patuelli, R., A. Reggiani, S. P. Gorman, P. Nijkamp and F. -J. Bade, 2007. Network Analysis of Commuting Flows: A Comparative Static Approach to German Data. Network Spatial Economics 7: 315-331. https://doi.org/10.1007/s11067-007-9027-6
  17. Tutzauer, F., 2007. Entropy as a measure of centrality in networks characterized by path-transfer flow. Social Networks 29: 249-265. https://doi.org/10.1016/j.socnet.2006.10.001