The KIPS Transactions:PartC (정보처리학회논문지C)

Korea Information Processing Society (한국정보처리학회)
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A Distributed Method for Bottleneck Node Detection in Wireless Sensor Network

무선 센서망의 병목 노드 탐색을 위한 분산 알고리즘

  • ;
  • 김진환 (부산대학교 컴퓨터공학과) ;
  • 유영환 (부산대학교 정보컴퓨터공학부)
  • Published : 2009.10.31
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Abstract

Wireless sensor networks (WSNs) have been considered as a promising method for reliably monitoring both civil and military environments under hazardous or dangerous conditions. Due to the special property and difference from the traditional wireless network, the lifetime of the whole network is the most important aspect. The bottleneck nodes widely exist in WSNs and lead to decrease the lifetime of the whole network. In order to find out the bottleneck nodes, the traditional centralized bottleneck detection method MINCUT has been proposed as a solution for WSNs. However they are impractical for the networks that have a huge number of nodes. This paper first proposes a distributed algorithm called DBND (Distributed Bottleneck Node detection) that can reduce the time for location information collection, lower the algorithm complexity and find out the bottleneck nodes quickly. We also give two simple suggestions of how to solve the bottleneck problem. The simulation results and analysis show that our algorithm achieves much better performance and our solutions can relax the bottleneck problem, resulting in the prolonging of the network lifetime.

무선 센서망은 위험이 존재하는 환경에서 공공 기관이나 군사적 목적의 신뢰성 있는 모니터링을 위한 수단으로 사용되어 왔다. 위험 상황이나 위험 물질이 존재하는 환경에서 사용된다는 특성 때문에, 망의 수명이 기존 무선망에서보다 더욱 중요한 성능 요소로 간주된다. 망 전체의 수명을 결정짓는 주요 요소 중 하나는 수명을 다하는 최초의 노드가 얼마나 이른 시간에 나타나느냐 하는 것이고, 이 최초의 노드는 망에 존재하는 병목 노드일 확률이 높다. 무선망의 병목 노드를 찾아내기 위한 방법으로 MINCUT 알고리즘이 대표적이나, 이는 중앙 집중형 방법이어서 많은 수의 노드로 이루어진 무선 센서망에는 적합하지 않다. 본 논문에서는 알고리즘의 계산 복잡도를 낮추어 매우 짧은 시간 내에 병목 노드를 탐지해 내는 분산형 방법을 제안한다. 수학적 분석과 실험을 통해 제안된 알고리즘이 기존 방법보다 훨신 향상된 성능을 보임을 확인할 수 있다.

Keywords

References

  1. I. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “A Survey on Sensor Networks,” IEEE Communications Magazine, Vol.40, No.8, pp.102-114, Aug., 2002. https://doi.org/10.1109/MCOM.2002.1024422
  2. Y. Yoo and D. P. Agrawal, “Mobile Sensor Relocation to Prolong the Lifetime of Wireless Sensor Networks,” in Proc. IEEE VTC‐Spring 2008, pp.193-197. https://doi.org/10.1109/VETECS.2008.52
  3. X. Ji and H. Zha, “Sensor Positioning in Wireless Ad hoc Sensor Networks Using Multidimensional Scaling,” in Proc. IEEE INFOCOM, 2004, pp.2652–2661.
  4. F. Y. S. Lin and P. L. Chiu, “A Near Optimal Sensor Placement Algorithm to Achieve Complete Coverage/Discrimination in Sensor Networks,” IEEE Communications Letters, Vol.9, No.1, Jan., 2005, pp.43-45. https://doi.org/10.1109/LCOMM.2005.01027
  5. Mechthild Stoer, Frank Wagner, “A Simple Min Cut Algorithm,” Journal of the ACM, Vol.44, No.4, July, 1997, pp.585–591. https://doi.org/10.1145/263867.263872
  6. Lizhi Xu et al., “Computer Mathematics of Modern Mathematics Handbook,” Huazhong University of Science and Technology Press, P539.
  7. Ningning Hu, Li (Erran) Li, Zhouqing Morley Mao, Peter Steenkiste and Jia Wang,“A Measurement Study of Internet Bottlenecks,” in Proc. IEEE INFOCOM 2005, pp.1689-1700. https://doi.org/10.1109/INFCOM.2005.1498450
  8. S. Floyd and V. Jacobson, “Random early detection gateways for congestion avoidance”. IEEE/ACM Transactions on Networking, Vol.1, No.4, pp.397-413, Aug., 1993. https://doi.org/10.1109/90.251892
  9. Heinzelman W. Application Specific protocol architectures for wireless networks [Ph.D. Thesis]. Boston: Massachusetts Institute of Technology, 2000.
  10. Handy MJ, Haase M, Timmermann D. Low energy adaptive clustering hierarchy with deterministic cluster head selection, In: Proc. of the 4th IEEE Conf, on Mobile and Wireless Communications Networks. Stockholm: IEEE Communications Society, 2002 https://doi.org/10.1109/MWCN.2002.1045790
  11. Haosong Gou, Gang Li and Younghwan Yoo, “A Partition Based Centralized LEACH Algorithm for Wireless Sensor Network Using solar Energy,” in Proceedings of the International conference on Convergence & Hybrid Information Technology 2009 (ICHIT 2009).
  12. Al Karaki JN, Ul Mustafa R, Kamal AE. Data aggregation in wireless sensor networks―Exact and approximate algorithms. In: Proc. of the IEEE Workshop on High Performance Switching and Routing. Phoenix: IEEE Communications Society, pp.241-245, 2004. https://doi.org/10.1109/HPSR.2004.1303478
  13. Younis O, Fahmy S. Heed: A hybrid, energy efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans. onMobile Computing, 3(4):660-669, 2004. https://doi.org/10.1109/INFCOM.2004.1354534