Journal of Advanced Navigation Technology (한국항행학회논문지)

The Korean Navigation Institute (한국항행학회)
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Fuzzy Relevance-Based Clustering for Routing Performance Enhancement in Wireless Ad-Hoc Networks

무선 애드 혹 네트워크상에서 라우팅 성능 향상을 위한 퍼지 적합도 기반 클러스터링

  • Lee, Chong-Deuk (Div. of Electronic Engineering, Chonbuk National University)
  • 이종득 (전북대학교 공과대학 전자공학부)
  • Received : 2010.05.04
  • Accepted : 2010.08.30
  • Published : 2010.08.31
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Abstract

The clustering is an important mechanism thai provides information for mobile nodes efficiently and improves the processing capacity for routing and the allocation of bandwidth. This paper proposes a clustering scheme based on the fuzzy relevance degree to solve problems such as node distribution found in the dynamic property due to mobility and flat structure and to enhance the routing performance. The proposed scheme uses the fuzzy relevance degree, ${\alpha}$, to select the cluster head for clustering in FSV (Fuzzy State Viewing) structure. The fuzzy relevance ${\alpha}$ plays the role in CH selection that processes the clustering in FSV. The proposed clustering scheme is used to solve problems found in existing 1-hop and 2-hop clustering schemes. NS-2 simulator is used to verify the performance of the proposed scheme by simulation. In the simulation the proposed scheme is compared with schemes such as Lowest-ID, MOBIC, and SCA. The simulation result showed that the proposed scheme has better performance than the other existing compared schemes.

클러스터링은 모바일 노드들에 대한 정보를 효율적으로 제공해 주며, 라우팅, 대역폭 할당과 같은 처리성능을 향상시키는 중요한 메카니즘이다. 본 논문에서 우리는 이동성(mobility)으로 인한 동적 속성, 평면구조 구조상에서 발생하는 노드 분산 등과 같은 문제를 효과적으로 해결하고 라우팅 성능을 향상시키기 위한 퍼지 적합도 기반의 클러스터링 기법을 제안한다. 제안된 기법은 FSV(Fuzzy_State_Viewing) 구조를 이용하여 퍼지 적합도${\alpha}$를 수행한다. 퍼지 적합도${\alpha}$는 FSV 구조에서 클러스터링을 수행하기 위한 클러스터헤드 CH(ClusterHead)를 선정하는 역할을 수행한다. 본 논문에서는 이와 같이 제안된 클러스터링 기법을 통해서 기존의 1-홉 클러스터 및 2-hop 클러스터에서 발생되는 문제를 해결하도록 하였다. 제안된 기법의 성능을 알아보기 위하여 우리는 NS-2 시뮬레이터를 이용하여 시뮬레이션을 수행하였다. 우리는 시뮬레이션 평가를 위해 기존의 Lowest-ID, MOBIC, SCA 기법 그리고 제안된 기법과의 성능을 비교하였다. 시뮬레이션 결과 제안된 기법의 성능이 Lowest-ID, MOBIC, SCA 기법에 비해서 우수함을 알 수 있다.

Keywords

References

  1. B. Kadri, A. Mohamed, M. Feham, "Secured Clustering for Mobile Ad Hoc Networks," IJCSNS International Journal of Computer Science and Network Security, VOL.7 No. 3, pp.27-34, 2007.
  2. Tim Daniel Hollerung, "The Cluster-Based Routing Protocol," project group Mobile Ad-Hoc Networks Based on Wireless LAN Winter semester 2003/2004.
  3. Minglian Jiang, Jinyang Li, Yong Chiang Tay, "Cluster Based Routing Protocol(CBRP) Functional Specification," IETF Internet Drift, draft-ieth-manet-corp-spec-00.txt, 1998.
  4. M. Chatterjee, Sajal K. Das and D. Turgut, "WCA A Weighted Clustering Algorithm for Mobile Ad Hoc Networks," Cluster Computing 5, pp. 193-204, 2002. https://doi.org/10.1023/A:1013941929408
  5. Tomoyuki Ohta, Shinji Inoue, and Yoshiaki Kakuda, "An Adaptive Multihop Clustering Science for Highly Mobile Ad Hoc Networks," Proceedings of the Sixth International Symposium on Autonomous Decentralized Systems(ISADS"03), pp. 1-8, 2003.
  6. C.R. Lin and M. Gerla, "Adaptive Clustering for Mobile Wireless Networks," IEEE Journal on Selected Areas in Communications, Vol. 15, No. 7, pp. 1265-1275, 1997. https://doi.org/10.1109/49.622910
  7. P. Basu, N. Khan, and T.D.C. Little, "A Mobility Based Metric for Clustering in Mobile Ad Hoc Networks," Proc. IEEE ICDCS 2001 Workshop on Wireless Networks and Mobile Chmputing, Phoenix AZ, pp. 1-19, 2001.
  8. Y. Wang, T. Liang, X. Yang and D. Zhang, "Scalable and Effective Cluster Based Routing Algorithm Using Node's Location for Mobile Ad Hoc Networks," Information Technology Journal 7(7): pp958-971, 2008. https://doi.org/10.3923/itj.2008.958.971
  9. K, Atanassov, "Intuitionistic Fuzzy Sets", Fuzzy Sets Syst. vol.20, pp.87-96, 1986. https://doi.org/10.1016/S0165-0114(86)80034-3
  10. NS-2 simulator, http://www.isi.edu/nanam/ns
  11. D. J. Baker and A. Ephremides, "The Architectural Organization of a Mobile Radio Network via a Distributed Algorithm," IEEE Transactions on Communications, 29(11), pp. 1694-1701, 1981. https://doi.org/10.1109/TCOM.1981.1094909
  12. I. F. Akyildiz, T. Melodia, T. R. Chowdhury," A suevey on wireless multimedia sensor networks", Computer Networks 51, pp. 921-960, 2007. https://doi.org/10.1016/j.comnet.2006.10.002
  13. P. Basu, N. Khan, and T. D. C. Little, "A Mobility Based Metric for Chustering in Mobile Ad Hoc Networks," Proc. IEEE ICDCSW 21st International Conference on Distributed Computing Systems Workshops, 2001.
  14. M. Chatterjee, Sajal, K. Das, and D. Turgut, "An Demand Weighed Clustering Algorithm(WCA) for Ad Hoc Networks," Global Telecommunications Conference, pp. 1697-1701, 2000.