近年來在無線感測網路 (Wireless sensor networks) 的研究中，目標物追蹤 (Target tracking) 是一項重要的研究議題。使用者利用無線感測器 (Wireless sensor nodes)，對欲監控之目標物進行監測，當目標物進入感測器的感測範圍後，感測器可取得所感測的資訊並回傳至後端之資料彙集點 (Sink node)。因此，使用者可以從資料彙集點取得所感測之資料。然而，有些應用只需要目標物進出某些區域之資訊。例如：動物學家欲了解某些野生動物，在廣大棲息地中遷徙或活動之習性，則可佈建無線感測網路做長期之監測，以取得寶貴之監測數據。本篇論文中，我們提出一種在無線感測網路中，分散式尋找出監測目標物之邊界點 (Boundary nodes) 的演算法。被選擇的邊界點將紀錄目標物進出邊界之時間資訊，並將這些資訊傳送至資料彙集點。模擬結果證明，我們所提出的演算法，所選出的邊界點數目相當接近最佳值。此外，我們的演算法所需要之控制封包數量也少於其他方法，且在網路範圍變大的情況下，使用我們的演算法來選擇邊界點之時間並不會增加太多。

In recent years, target tracking has been an important issue in research of wireless sensor networks. Users can use wireless sensor networks to keep the interesting target under surveillance. Once the target enters the sensing range of the sensor node, the sensing information will be recorded by the sensor nodes and forwarded to the sink node. Therefore, users can obtain the information from the sink node. However, some applications only need to record the information of a target entering or leaving a boundary for some specific regions. For example, zoologists want to know some kinds of wildlife migration or habitual behavior in a large-scale natural habitat, and then they can deploy a wireless sensor network to keep a long-term surveillance and get precious monitoring data. In this thesis, we proposed a distributed algorithm to find out the boundary nodes in a wireless sensor network. The selected boundary nodes are used to track the interesting targets (wildlife) when they enter or leave a boundary of the wireless sensor network. The information of wildlife entering or leaving the monitoring regions will be recorded and forwarded to the sink node by the boundary sensor nodes. Simulation results show that the proposed protocols have good performance in selecting boundary nodes. The number of selected boundary nodes almost closes to the optimal value. Besides, our protocol has the less total control overhead during selecting boundary nodes. As the size of the wireless sensor network is increasing, the time of selecting the boundary nodes using our protocol will not increase rapidly in our protocol.

[1] H. T. Kung and D. Vlah, “Efficient Location Tracking Using Sensor Networks,” in Proceedings of the Wireless Communications and Networking, Vol.3, pp. 1954 - 1961, New Orleans, Louisiana, USA, Mar. 2003.
[2] H. Yang and B. Sikdar, “A protocol for tracking mobile targets using sensor networks,” in Proceedings of the First IEEE Workshop on Sensor Network Protocols and Applications, pp. 71 - 81, Anchorage, Alaska, USA, May 2003.
[3] J. Liu, M. Chu, J. Liu, J. Reich, and F. Zhao, “Distributed State Representation for Tracking Problems in Sensor Networks,” in Proceedings of the Third International Symposium on Information Processing in Sensor Networks, pp. 234-242, Berkeley, California, USA, Apr. 2004.
[4] J. Aslam, Z. Butler, F. Constantin, V. Crespi, G. Cybenko, and D. Rus, “Tracking a Moving Object with a Binary Sensor Network,” in Proceedings of the First International Conference on Embedded Networked Sensor Systems, pp. 150-161, Los Angeles, California, USA, Nov. 2003.
[5] K. Mechitov, S. Sundresh, Y. Kwon, and G.. Agha, “Cooperative Tracking with Binary-Detection Sensor Networks,” in Proceedings of the First International Conference on Embedded networked sensor systems, pp. 332-333, Los Angeles, California, USA, Nov. 2003
[6] R.Gupta and S. R. Das, “Tracking Moving Targets in a Smart Sensor Network,” in Proceeding of the VTC Fall 2003 Symposium, Vol. 5, pp. 3035-3039, Orlando, Florida, USA, Oct. 2003.
[7] Y. Xu, J. Winter, and W.-C. Lee, “Prediction Based Strategies for Energy Saving in Object Tracking Sensor Networks,” in Proceedings of the IEEE International Conference on Mobile Data Management, pp. 346-357, Berkeley, California, USA, Jan. 2004.
[8] Y. Xu, J. Winter, and W.-C. Lee, “Dual Prediction-based Reporting Mechanism for Object Tracking Sensor Networks,” in Proceedings of the First Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services, pp. 154-163, Boston, Massachusetts, USA, Aug. 2004.
[9] Y. Xu and W.-C. Lee, “On Localized Prediction for Power Efficient Object Tracking in Sensor Networks,” in Proceedings of International Workshop on Mobile Distributed Computing, pp. 434-439, Providence, Rhode Island, May 2003.
[10] W. Zhang and G. Cao, “DCTC：Dynamic Convoy Tree-Based Collaboration for Target Tracking in Sensor Networks,” IEEE Transactions on Wireless Communications, Vol. 3, pp. 1689-1701, Sep. 2004.
[11] W. Zhang and G. Cao, “Optimizing Tree Reconfiguration for Mobile Target Tracking in Sensor Networks,” in Proceedings of IEEE INFOCOM 2004, Vol. 4, pp.2434-2445, Hong Kong, China, Mar. 2004.
[12] X. Ji and H. Zha, “Sensor Positioning in Wireless Ad-hoc Sensor Networks Using Multidimensional Scaling,” in Proceedings of IEEE INFOCOM 2004, Vol. 4, pp. 2652-2661, Hong Kong, China, Mar. 2004.
[13] J. C. Navas and T. Imielinski, “Geocast-geographic addressing and routing,” in Proceedings of the Third Annual ACM/IEEE International Conference on Mobile Computing and Networking, pp. 66-76, Budapest, Hungary, Sept. 1997.
[14] W.-H. Liao, Y.-C. Tseng, K. L. Lo, and J.-P. Sheu, "Geo GRID: A Geocasting Protocol for Mobile Ad Hoc Networks Based on GRID," Journal of Internet Technology, Vol. 1, No. 2, pp. 23-32, Dec. 2000.
[15] W.-H. Liao, Y.-C. Tseng, and J.-P. Sheu, "GRID: A Fully Location-Aware Routing Protocol for Mobile Ad Hoc Networks," Telecommunication Systems, Vol. 18, No. 1, pp. 37 – 60, Sep. 2001.