무선 센서 네트워크에서의 연속적인 물체의 추적을 위한 에너지 효율적인 경계 선정 기법

An Energy-efficient Edge Detection Method for Continuous Object Tracking in Wireless Sensor Networks

  • 장상욱 (홍익대학교 컴퓨터공학과) ;
  • 한주선 (홍익대학교 컴퓨터공학과) ;
  • 하란 (홍익대학교 컴퓨터공학과)
  • 발행 : 2009.12.15

초록

무선 센서 네트워크는 군사적, 환경적 목적으로 다방면에서 활용될 수 있는데, 최근 유독가스, 산불, 지진과 같은 연속적인 성격을 가진 물체의 확산 경로를 추적하는 연구가 새롭게 진행되고 있다. 기존 연구에서는 연속적인 물체의 경계를 지역적으로 측정하기 위해 1-홉 이웃 노드들과의 통신을 통한 방식을 제시하였으나, 이러한 방식은 불필요하게 많은 노드들이 경계 노드로 선택되어 물체의 경계를 정확히 측정할 수 없는 문제를 안고 있다. 본 논문에서는 최소한의 경계 노드를 선별하기 위해 지역적인 드로네 삼각기법을 이용한 방법을 제안하고, 연속적인 물체를 에너지 효율적으로 추적하기 위한 센서의 동작 규칙을 규정한다. 모의실험 결과, 본 논문에서 제안한 방법이 기존의 1-홉 경계 설정과 비교해 경계 노드의 선택 정확도는 평균 29.95% 개선되면서도 경계 노드의 수는 평균 54.43% 감소하며, 통신 메시지 수와 에너지 소모량은 각각 평균 79.36%, 72.34% 향상됨을 보였다. 또한, MICAz mote를 이용한 현장실험을 통해 평균 48.38% 경계 노드 수가 감소함을 보였다.

Wireless sensor networks (WSNs) can be used in various applications for military or environmental purpose. Recently, there are lots of on-going researches for detecting and tracking the spread of continuous objects or phenomena such as poisonous gas, wildfires, earthquakes, and so on. Some previous work has proposed techniques to detect edge nodes of such a continuous object based on the information of all the 1-hop neighbor nodes. In those techniques, however, a number of nodes are redundantly selected as edge nodes, and thus, the boundary of the continuous object cannot be presented accurately. In this paper, we propose a new edge detection method in which edge nodes of the continuous object are detected based on the information of the neighbor nodes obtained via the Localized Delaunay Triangulation so that a minimum number of nodes are selected as edge nodes. We also define the sensor behavior rule for tracking continuous objects energy-efficiently. Our simulation results show that the proposed edge detection method provides enhanced performance compared with previous 1-hop neighbor node based methods. On the average, the accuracy is improved by 29.95% while the number of edge nodes, the amount of communication messages and energy consumption are reduced by 54.43%, 79.36% and 72.34%, respectively. Moreover, the number of edge nodes decreases by 48.38% on the average in our field test with MICAz motes.

키워드

참고문헌

  1. Ji, X., Zha, H., Metzner, J. J., and Kesidis, G., "Dynamic Cluster Structure for Object Detection and Tracking in Wireless Ad-Hoc Sensor Net works," in Proceedings of the 2004 IEEE Inter national Conference on Communications, vol.7, pp 3807-3811, 2004
  2. Chintalapudi, K. K. and Govindan, R., "Localized Edge Detection in Sensor Fields," in Proceedings af the 1st IEEE Sensor Network Protocols and Applications, pp.59-70, 2003
  3. Chang, W.-R., Lin, H.-T., and Cheng, Z.-Z., "CODA: A Continuous Object Detection and Tracking Algorithm for Wireless Ad Hoc Sensor Networks," in Proceedings af the gh IEEE Consumer Communications and Networking Conference, pp.168-174, 2008
  4. Fang, Q., Gao, J., and Guibas, L. J., "Locating and Bypassing Routing Holes in Sensor Networks," Mobile Networks and Applications, vol.11, no.2, pp.187-200, 2006 https://doi.org/10.1007/s11036-006-4471-y
  5. Zhang, C., Zhang, Y., and Fang, Y., "Detecting Coverage Boundary Nodes in Wireless Sensor Networks," in Proceedings of the 2006 IEEE International Conference on Networking, Sensing and Control, pp.868-873, 2006
  6. Zhang, C., Zhang, Y., and Fang, Y., "Localized Algorithms for Coverage Boundary Detection in Wireless Sensor Networks," Wireless Networks, vol.15, no.1, pp.3-20, 2009 https://doi.org/10.1007/s11276-007-0021-1
  7. Savvides, A., Han, C. C., and Strivastava, M. B., "Dynamic Fine-Grained Localization in Ad-Hoc Networks of Sensors," in Proceedings of the 7th Annual International Conference on Mobile Computing and Networking, pp.166-179, 2001
  8. Moore, D., Leonard, J., Rus, D., and Teller, S., "Robust Distributed Network Localization with Noisy Range Measurements," in Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems, pp.50-61, 2004
  9. Cheng, X., Thaeler, A., Xue, G., and Chen, D., "TPS: A Time- Based Positioning Scheme for Outdoor Wireless Sensor Networks," in Proceedings of the 22rd Annual Joint Conference of the IEEE Computer and Communication Societies, vol.4, pp.2685-2696, 2004
  10. Maroti, M., Kusy, B., Simon, G., and Ledeczi, A., "The Flooding Time Synchronization Protocol," in Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems, pp.39-49, 2004
  11. Werner-Allen, G. and Tewari, G., "Firefly-Inspired Sensor Network Synchronicity with Realistic Radio Effects," in Proceedings of the 3rd International Conference on Embedded Networked Sensor Systems, pp.142-153, 2005
  12. Ganeriwal, S., Kumar, R., and Strivastava. M. B., "Timing-Sync Protocol for Sensor Networks," in Proceedings af the 1st International Conference on Embedded Networked Sensor Systems, pp.138-149, 2003
  13. Intanagonwiwat, C., Gobindan, R., Estrin, D., and Heidenmann, J., "Directed Diffusion for Wireless Sensor Networking," IEEE/ACM Transactions on Networking, vol.11, no.1, pp.2-16, 2003 https://doi.org/10.1109/TNET.2002.808417
  14. He, T., Krishnamurthy, S., Stankovic, J. A., and Abdelzaher, T., "Energy-Efficient Surveillance System Using Wireless Sensor Networks," in Proceedings of the 2nd International Conference on Mobile Systems, Applications, and Services, pp270-283, 2004