한국정보통신학회논문지 (Journal of the Korea Institute of Information and Communication Engineering)

  • 제17권9호
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  • Pages.2020-2028
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  • 2013
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  • 2234-4772(pISSN)
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  • 2288-4165(eISSN)
한국정보통신학회 (The Korea Institute of Information and Commucation Engineering)
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복잡계 네트워크기반 무선 애드혹 네트워크 설계 및 분석

Design and Analysis of Wireless Ad Hoc Networks Based on Theory of Complex Networks

  • Jung, Bang Chul (Department of Information and Communication Engineering, Gyeongsang National University) ;
  • Kang, Kee-Hong (College of Humanities & Social Sciences, Seoul National University of Science and Technology) ;
  • Kim, Jeong-Pil (Department of Chinese Language and Literature, Gyeongsang National University) ;
  • Park, Yeon-Sik (Department of Information and Communication Engineering, Gyeongsang National University)
  • 투고 : 2013.07.09
  • 심사 : 2013.09.04
  • 발행 : 2013.09.30
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초록

본 논문에서는 복잡계 네트워크 이론에 기반하여 무선 애드혹 네트워크를 분석하고 네트워크 토폴로지를 구성하는 방법에 관하여 제안한다. 본 논문에서는 기존의 복잡계 네트워크 연구가 무선 통신 채널의 특성을 정확히 반영하지 못한 부분을 개선하였으며, 랜덤 그래프 이론을 무선 통신 환경을 고려하여 확장하였다. 주요 결과로서 복잡계 네트워크 이론에 기반한 네트워크 토폴로지 구성이 전체 애드혹 네트워크 성능에 미치는 영향을 분석하고 시뮬레이션을 통하여 검증하였다.

In this paper, we propose a novel analysis and design methodology based on complex network theory for wireless large-scale ad hoc networks. We also enhance the conventional analysis methods which does not sufficiently consider the effect of the wireless communication channels and extend the existing random graph theory by reflecting the wireless communication environments. As a main result, the effect of the network topology such as average degree of each communication node on the network capacity through extensive computer simulations.

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참고문헌

  1. CISCO, "Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2012-2017, White paper, Feb. 2013.
  2. IEEE 802.16-10/0004r3, "IEEE 802.16p machine to machine (M2M) system requirements document (SRD)", Std. Sep. 2011.
  3. M. Chui, M. Loffler, and R. Roberts, "The internet of things," McKinsey Quarterly, Mar. 2011.
  4. 3GPP TR 22.868 V8.0.0, Tech. Spec. Group Services and System Aspects, Study on Facilitating Machine to Machine Communication in 3GPP Systems, (Release 8), 3GPP Std., Dec. 2008.
  5. IEEE C80216-10-002r7 "Machine to Machine (M2M) Communication Study Report", IEEE 802.16 Contribution, May. 2010.
  6. P. Gupta and P. R. Kumar, "Capacity of wireless networks," IEEE Transactions on Information Theory, Vol. 46, No. 2, pp. 388-404, March 2000. https://doi.org/10.1109/18.825799
  7. A. L. Barabasi and R. Albert, "Emergence of scaling in random networks," Science, Vol. 286, pp. 509-512, 1999. https://doi.org/10.1126/science.286.5439.509
  8. R. Albert, H. Jeong, and A. L. Barabasi, "Error and attack tolerance of complex networks," Nature, Vol. 406, pp. 378 -382, 2000. https://doi.org/10.1038/35019019
  9. F. Saffre, H. Jovanovic, C. Hoile, and S. Nicolas, "Scale-free topology for pervasive network," BT Technology J., Vol. 22, pp. 200-208, Jul. 2004. https://doi.org/10.1023/B:BTTJ.0000047133.25088.4f
  10. L. Wang, H. Jin, J. Dang, and Y. Jin, "A fault tolerant topology control algorithm for large-scale sensor networks," in Proc. International Conference on Parallel and Distributed Computing, pp. 407-412, Nov. 2007.
  11. Y. -B, Kim, B. Hong, W. Choi, "Scale-freee wireless networks with limited degree information," IEEE Wireless Communications Letters, Vol. 1, No. 5, pp. 428-431, Oct. 2012. https://doi.org/10.1109/WCL.2012.061212.120309
  12. L. Kleinrock, Queueing systems - Volume 1: Theory, Wiley, 1975.