DOI QR코드

DOI QR Code

센서 네트워크 클러스터링 기법의 데이터 예측 전략

Data prediction Strategy for Sensor Network Clustering Scheme

  • 최동민 (조선대학교 컴퓨터공학과) ;
  • 심검 (조선대학교 컴퓨터공학과) ;
  • 모상만 (조선대학교 컴퓨터공학부) ;
  • 정일용 (조선대학교 컴퓨터공학부)
  • 투고 : 2011.06.16
  • 심사 : 2011.08.11
  • 발행 : 2011.09.30

초록

센서 네트워크 클러스터링 기법은 네트워크의 수명연장에 효율적인 방법이다. 그러나 이 방법은 센서노드의 수집 데이터가 중복되기 쉬운 환경에서 적용할 경우 중복된 데이터 전송에 불필요하게 에너지가 소모된다는 문제점이 있다. 이에 본 논문은 중복되는 데이터 전송을 배제하고 클러스터 헤드 노드와 멤버노드 사이의 전송을 최소화하기 위해 센서 노드가 수집하는 데이터를 예측할 수 있는 데이터 예측 기법을 제안하였다. 이 방법은 인접노드의 중복데이터 수집을 배제하여 에너지 효율적인 데이터 전송이 가능하다. 여기에 불필요한 전송을 줄이기 위해 데이터 예측 그래프를 이용하여 수집 데이터 분석을 통한 선택적인 전송을 하는 방법을 도입하였다. 성능분석 결과에 의하면 제안하는 방법은 기존의 클러스터링 방법에 비해 노드들의 에너지 소모가 줄어들었다. 그럼에도 불구하고 전송 효율과 수집 데이터의 정확도가 증가했으며 결과적으로 네트워크 수명이 증가하였다.

Sensor network clustering scheme is an efficient method that prolongs network lifetime. However, when it is applied to an environment in which collected data of the sensor nodes easily overlap, sensor node unnecessarily consumes energy. Accordingly, we proposed a data prediction scheme that sensor node can predict current data to exclude redundant data transmission and to minimize data transmission among the cluster head node and member nodes. Our scheme excludes redundant data collection by neighbor nodes. Thus it is possible that energy efficient data transmission. Moreover, to alleviate unnecessary data transmission, we introduce data prediction graph whether transmit or not through analyze between prediction and current data. According to the result of performance analysis, our method consume less energy than the existing clustering method. Nevertheless, transmission efficiency and data accuracy is increased. Consequently, network lifetime is prolonged.

키워드

참고문헌

  1. G.J. Pottie and W.J. Kaiser, "Wireless Integrated Network Sensors," Communications of the ACM, Vol.43(5), pp. 51-58, 2000. https://doi.org/10.1145/332833.332838
  2. Y. Yao, and J. Gehrke, "Query Processing for Sensor Networks," In Proc. Conf. Innovative Data Systems Research, 2003.
  3. J. Al-karaki and A. Kamal, "Routing Techniques in Wireless Sensor Networks: A Survey," IEEE Wireless Communications, Vol.11, pp. 6-28, 2004.
  4. Y. Tseng, S. Ni, Y. Chen, and J. Sgeu, "The Broadcast Strom Problem in a Mobile Ad Hoc Network," The Journal of Mobile Communication Computation and Information, Vol.8, No.1-2, pp. 153-167, 2002.
  5. Li Jian and P. Mohapatra, "An Analytical Model for the Energy Hole Problem in Manyto- one Sensor Networks," Proceedings of Vehicular Technology Conference 2005 IEEE 62nd, Vol.4, pp. 2721-2725, 2005.
  6. X. Wu, G. Chen, and S. Das, "Avoiding Energy Holes in Wireless Sensor Networks with Nonuniform Node Distribution," IEEE Transactions on Parallel and Distributed Systems, Vol.19, No.5, pp. 710-720, 2008. https://doi.org/10.1109/TPDS.2007.70770
  7. W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, "Energy-Efficient Communication Protocol for Wireless Microsensor Networks," System Sciences, 2000. Proceedings of the 33rd Annual Hawaii International Conference on, Vol.2, pp. 10, 2000.
  8. W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, "An Application-Specific Protocol Architecture for Wireless Microsensor Networks," IEEE Transactions on Wireless Communications, Vol.1, pp. 660-670, 2002. https://doi.org/10.1109/TWC.2002.804190
  9. O. Younis and S. Fahmy, "Distributed Clustering in Ad-hoc Sensor Networks: A Hybrid, Energy-Efficient Approach," INFOCOM 2004. Twenty-third AnnualJoint Conference of the IEEE Computer and Communications Societies, pp. 629-640, 2004.
  10. S.D. Muruganathan, D.C.F. Ma, R.I. Bhasin, and A.O. Fapojuwo, "A Centralized Energy-Efficient Routing Protocol for Wireless Sensor Networks, IEEE Communications Magazine, Vol.43, pp. s8-s13, 2005.
  11. A. Manjeshwar and D. P. Agarwal, "TEEN: a Routing Protocol for Enhanced Efficiency in Wireless Sensor Networks," Parallel and Distributed Processing Symposium, Proceedings 15th International, pp. 30189, 2001.
  12. A. Manjeshwar and D. P. Agarwal, "APTEEN: A Hybrid Protocol for Efficient Routing and Comprehensive Information Retrieval in Wireless Sensor Networks," Parallel and Distributed Processing Symposium, Proceedings International, IPDPS 2002, pp. 195-202, 2002.
  13. Dongmin Choi, Sangman Moh, and Ilyong Chung, "Regional Clustering Scheme in Densely Deployed Wireless Sensor Networks for Weather Monitoring Systems," The 12th IEEE International conference on High Performance Computing and Communications 2010, pp. 497-502, 2010.
  14. N. Bouabdallah, M.E. Rivero-Angeles, and B. Sericola, "Continuous Monitoring Using Event- Driven Reporting for Cluster-Based Wireless Sensor Networks," Vehicular Technology, IEEE Transactions on, Vol.58, pp. 3460- 3479, 2009. https://doi.org/10.1109/TVT.2009.2015330
  15. 최동민, 모상만, 정일용 "무선 센서 네트워크 환경의 Threshold-sensitive 가변 영역 클러스터링 프로토콜에 관한 분석", 멀티미디어학회 논문지, Vol.12, No.11, pp. 1609-1622, 2009.

피인용 문헌

  1. Data-centric Energy-aware Re-clustering Scheme for Wireless Sensor Networks vol.17, pp.5, 2014, https://doi.org/10.9717/kmms.2014.17.5.590
  2. Impact of Sink Node Location in Sensor Networks: Performance Evaluation vol.17, pp.8, 2014, https://doi.org/10.9717/kmms.2014.17.8.977
  3. An Analysis of the Impact of Different Types of Sensors on Wireless Sensor Networks vol.19, pp.9, 2014, https://doi.org/10.9708/jksci.2014.19.9.075
  4. Energy Efficient Clustering Scheme for Multi-sensor on Wireless Sensor Networks vol.19, pp.3, 2016, https://doi.org/10.9717/kmms.2016.19.3.573
  5. 모바일 애드혹 네트워크에서 클러스터의 페어 헤드 노드를 이용한 향상된 CBRP vol.16, pp.1, 2011, https://doi.org/10.9717/kmms.2013.16.1.056
  6. 센서 네트워크에서 모바일 싱크를 위한 효율적인 라우팅 기법 vol.20, pp.4, 2011, https://doi.org/10.9717/kmms.2017.20.4.640