The Journal of Korean Institute of Communications and Information Sciences (한국통신학회논문지)

The Korean Institute of Commucations and Information Sciences (한국통신학회)
권호 표지
DOI QR코드

DOI QR Code

Continuous Moving Object Tracking Using Query Relaying in Tree-Based Sensor Network

트리 기반의 센서 네트워크에서 질의 중계를 통한 이동 객체의 연속적인 위치 획득 방안

  • Received : 2014.02.24
  • Accepted : 2014.05.08
  • Published : 2014.05.31
Download PDF
⟨ Previous Next ⟩

Abstract

In wireless sensor networks, there have been two methods for sensing continuously moving object tracking: user-query based method and periodic report based method. Although the former method requires overhead for user query rather than the latter method, the former one is known as an energy-efficient method without transferring unnecessary information. In the former method, a virtual tree, consisting of sensor nodes, is exploited for the user querying and sensor reporting. The tree stores the information about mobile objects; the stored information is triggered to report by the user query. However, in case of fast moving object, the tracking accuracy reduces due to the time delay of end-to-end repeated query. To solve the problem, we propose a query relaying method reducing the time delay for mobile object tracking. In the proposed method, the nodes in the tree relay the query to the adjacent node according to the movement of mobile object tracking. Relaying the query message reduces the end-to-end querying time delay. Simulation results show that our method is superior to the existing ones in terms of tracking accuracy.

무선 센서 네트워크에서 이동 객체를 감지하기 위해 질의를 통해 위치를 획득하는 방법과 객체 감지 시 설정된 싱크로 보고받는 방법이 있다. 전자의 질의/응답 형태의 네트워크는 후자에 비해 사용자의 질의/응답에 따른 오버헤드가 있지만, 불필요한 정보 전달이 없으므로 에너지 효율적이다. 최근 질의/응답 형태의 연구들은 가상의 트리를 구성하여 질의를 하는 방법을 사용한다. 이동객체가 움직이는 네트워크에서 가상의 트리는 이동객체의 정보만을 트리에 가지고 있으며, 질의가 발생하면 트리에 저장된 정보를 참조하여 객체의 위치정보를 반환한다. 하지만 빠르게 움직이는 객체를 연속적으로 추적하는 경우, 다량의 질의 발생으로 인한 에너지 문제와 이동 객체의 속도에 따라 질의/응답 과정의 시간 지연으로 추적 정밀도 하락문제가 발생한다. 이러한 문제는 질의를 싱크에서만 하는 것으로부터 발생한다. 본 논문에서는 효율적인 이동 객체 추적을 위하여 싱크에서 시작된 질의를 각 리프노드가 이동 객체의 예상 경로에 중계함으로써 질의 경로를 줄이는 방안을 제시한다. 시뮬레이션을 통해 기존의 방법들에 비해 더 나은 에너지 효율 및 정밀성을 가진다는 것을 증명한다.

Keywords

References

  1. I. F. Akyildiz, et al., "A survey on sensor networks," IEEE Commun., vol. 40, no. 8, pp. 102-114, Aug. 2002.
  2. E. B. Hamida and G. Chelius, "Strategies for data dissemination to mobile sinks in wireless sensor networks," IEEE Trans. Wirel. Commun., vol. 15, no. 6, pp. 31-37, Dec. 2008.
  3. B. Anggorojati, et al., "Efficient and scalable location and mobility management of EPCglobal RFID system," WPMC, pp. 1-6, Atlantic City, NJ, Jun. 2013.
  4. M.-C. Chung, et al., "RFID Object Tracking with IP Compatibility for the Internet of Things," GreenCom, pp. 132-139, Besancon, Nov. 2012.
  5. H. T. Kung and D. Vlah, "Efficient location tracking using sensor networks," WCNC, pp. 1954-1961, New Orleans, LA, USA, Mar. 2003.
  6. C.-Y. Lin and Y.-C. Tseng. "Structures for in-network moving object tracking in wireless sensor networks," BROADNETS, pp. 718- 727, San Jose, California, USA, Oct. 2004.
  7. E. S. Lee, et al., "On-demand geographic routing protocol in wireless sensor networks," J. KISS, vol. 15, no. 7, pp. 495-499, Jul. 2009.
  8. G. Wang, M. Z. A. Bhuiyan, J. Cao, and J. Wu, "Detecting movements of a target using face tracking in wireless sensor networks," IEEE Trans. Parallel and Distributed Syst., vol. 25, no. 4, pp. 939-949, Mar. 2013.
  9. J. Hightower and G. Borriello, "Location systems for ubiquitous computing," IEEE Computer, vol. 34, no. 8, pp. 57-66, Aug. 2001.
  10. E. S. Lee, et al., "Sink location dissemination scheme in geographic routing for wireless sensor networks," J. KICS, vol. 34, no. 9, pp. 847-856, Sept. 2009.
  11. N. Bulusu, J. Heidemann, and D. Estrin, "GPS-less low cost outdoor localization for very small devices," IEEE Personal Commun. Mag., vol. 7, no. 5, pp. 28-34, Oct. 2000.
  12. W. S. Lee, H. S. Hong, and S. H. Kim, "Cluster-based continuous object prediction algorithm for energy efficiency in wireless sensor networks," J. KICS, vol. 36, no. 8, pp. 489-496, Aug. 2011. https://doi.org/10.7840/KICS.2011.36C.8.489
  13. J.A. Bondy and U.S.R. Murty, Graph theory with applications, North-Holland: Elsevier, 1976.
  14. O. Younis, M. Krunz, and S. Ramasubramanian, "Node clustering in wireless sensor networks: Recent Developments and Deployment Challenges," IEEE Network Mag., vol. 20, no. 3, pp. 20-25, May/Jun. 2006. https://doi.org/10.1109/MNET.2006.1637928
  15. S. Bandyopadhyay and E. Coyle, "An energyefficient hierarchical clustering algorithm for wireless sensor networks," in Proc. IEEE INFOCOM, pp. 1713-1723, San Francisco, California, USA, Apr. 2003.
  16. Younis and S. Fahmy, "HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks," IEEE Trans. Mobile Computing, vol. 3, no. 4, pp. 366-379, Oct./Dec. 2004. https://doi.org/10.1109/TMC.2004.41
  17. E. Masazade, R. Niu, P. K. Varshney, and M. Keskinoz, "Energy aware iterative source localization schemes for wireless sensor networks," IEEE Trans. Signal Process., vol. 58, no. 9, pp. 4824-4835, Sept. 2010 https://doi.org/10.1109/TSP.2010.2051433
  18. Scalable Network Technologies, Qualnet, [online]. Available: http://www.scalable-networks.com
  19. J. Hill and D. Culler, "Mica: A wireless platform for deeply embedded networks," IEEE Micro, vol. 22, no. 6, pp. 12-24, Nov./Dec. 2002.