無線感測網路的出現啟發了許多觀察物理環境與透過計算設備自動取得有用資訊之應用，偵測目標物或事件是否存在於感測範圍內，為無線感測網路中最重要的應用之一，而感測節點之佈署情形為影響偵測時間之一大主因，因此，在實行相關偵測應用前，各個感測節點之佈署必須被慎重考慮，才能進一步有效實行各種應用。在過去大多數的研究中，則使用了簡易的二元偵測當作偵測目標物的模型，根據一特定感測節點特定時間之感測資訊判斷，並將此判斷結果視為整個網路所執行的決定。然而，如此簡易的偵測策略容易導致較高的誤警機率(false alarm probability)並且減低偵測效能(detection performance)。此篇論文中，我們首先提出一個基於概似比值檢定(Likelihood ratio test)的合作連續偵測機制，並且分析偵測目標物是否存在之偵測延遲時間(detection latency)，接著再根據此偵測延遲時間分別應用於其他感測節點佈署方法，找出感測節點適當佈署的位置，使得目標物可能存在之任何位置，皆能讓最差的偵測延遲時間達到最短。貪婪佈署藉由在每一次的佈署週期中，選擇偵測延遲時間最長之位置佈署感測節點，得到較短的偵測延遲時間，但卻產生非常高的通訊成本；Se-Grid把整個偵測區域分割成各自獨立的格子群組，降低了通訊成本，但也因為各個感測節點只參與各自所屬格子群組之偵測，使得偵測延遲時間變長；相較之下，Co-Grid透過重疊之虛擬格子以及格子群組間相互之合作，不僅降低通訊成本，同時也得到較短的偵測延遲時間。最後的實驗結果驗證經由分析而得之偵測延遲時間與模擬實際情形得到的偵測延遲時間非常接近；而在感測節點佈署之實驗模擬中，我們分別以障礙物存在與否之情況下進行模擬，從模擬結果顯示出Se-Grid降低了通訊成本，但卻增加所需之偵測延遲時間；而Co-Grid在增加通訊成本之情況下，能夠得到較好之偵測延遲時間。

The emergence of wireless sensor networks has given the ability to many applications to observe the physical environment automatically. One of the most important applications of wireless sensor networks is to detect a target or event in a region of interest and the detection performance such as the latency of detection is affected by sensor deployment dramatically. Most of prior studies for target detection assume that each sensor node performs the detection tasks independently using a simple binary detection model. This trivial detection strategy may result in high false alarm probability and deteriorate the detection performance. This paper proposes a collaborative sequential detector based on Likelihood ratio test and analytically derives the detection latency. Based on detection latency, we present three sensor deployment protocols that can minimize the worst-case detection latency over all possible locations of the target. The greedy deployment derives lower detection latency by placing sensor nodes on the location of highest latency iteratively. However, it could introduce very large communication overhead. By dividing the field into independent regions, the Se-Grid protocol reduces communication overhead, but increases detection latency since only sensors in one separate region participate detection operations. In contrast, the Co-Grid protocol reduces communication overhead and the detection latency by coordinating overlapping virtual grids and organizing the network into fusion groups. Simulations are conducted to verify the analytical solution for detection latency. The performance of the proposed sensor deployment methods are also evaluated by simulations with and without the presence of obstacles. From the simulations, Se-Grid reduces communication overhead but increase detection latency. In contrast, Co-Grid gets better detection latency performance with the cost of increasing communications.

[1]. D. Estrin, L. Girod, G. Pottie, and M. Srivastava, “Instrumenting the World with Wireless Sensor Networks,” in Proc. of ICASSP, vol. 4, 2001, pp. 2003-2036.
[2]. T. Yan, T. He, and J.A. Stankovic, “Differentiated Surveillance for Sensor Networks,” in Proc. of the 1st international conference on Embedded networked sensor systems, pp. 62-74, 2003.
[3]. J. Chen, S. Kher, and A. Somani, “Distributed Fault Detection of Wireless Sensor Networks,” in Proc. of the workshop on Dependability issues in wireless ad hoc networks and sensor networks, pp. 72-79, 2006.
[4]. X. Hong, Kaixin Xu, and M. Gerla, “Scalable Routing Protocols for Mobile Ad Hoc Networks,” IEEE network, 16(4):11-21, 2002.
[5]. Y. Xu, J. Heidemann, and D. Estrin, “Geography-informed Energy Conservation for Ad Hoc Routing,” in Proc. of the 7th annual international conference on Mobile computing and networking, pp. 84-99, ACM, 2001.
[6]. G. Xing, X. Chang, C. Lu, J. Wang, K. Shen, R. Pless, and J.A. O’Sullivan, “Efficient Coverage Maintenance Based on Probabilistic Distributed Detection,” IEEE transaction on Mobile computing, Sep. 2010.
[7]. X. Bai, S. Kuma, D. Xua, Z. Yun, and T. H. Lai, “Deploying Wireless Sensors to Achieve Both Coverage and Connectivity,” in Proc. ACM MobiHoc, May 2006.
[8]. O. Dousse, C. Tavoularis, and P. Thiran, “Delay of Intrusion Detection in Wireless Sensor Networks,” in Proc. ACM Mobihoc, May 2006.
[9]. M. Duarte, and Y. H. Hu, “Distance Based Decision Fusion in A Distributed Wireless Sensor Network,” Telecommunication Systems, vol. 26, no. 2-4, 2004.
[10]. G. Yang, V. Shukla, and D. Qiao, “A Novel On-Demand Framework for Collaborative Object Detection in Sensor Networks,” IEEE INFOCOM, 2008.
[11]. R. Tan, G. Xing, J. Wang, and H. C. So, “Collaborative Target Detection in Wireless Sensor Networks with Reactive Mobility,” IWQoS, 2008.
[12]. L. Yu, L. Yuan, G. Qu, and A. Ephremides, “Energy-Driven Detection Scheme with Guaranteed Accuracy,” in Proc. IPSN, 2006.
[13]. T.P. Lambrou and C.G. Panayiotou, “Collaborative Event Detection Using Mobile and Stationary Nodes in Sensor Networks,” CollaborateCom, 2007.
[14]. A. Howard, M. J. Mataric, and G. S. Sukhatme, “An Incremental Self- Deployment Algorithm for Mobile Sensor Networks,” Autonomous Robots, 13(2):113-126, 2002.
[15]. A. Howard, M. J. Mataric, and G. S. Sukhatme, “Mobile Sensor Network Deployment using Potential Fields: A Distributed, Scalable Solution to the Area Coverage Problem,” in Proc. of DARS, pp. 299- 308, 2002.
[16]. S. Abdel-Mageid and R.A. Ramadan, “Efficient Deployment Algorithms for Mobile Sensor Networks,” Autonomous and Intelligent Systems (AIS), 2010.
[17]. A. Ababnah and B Natarajan, “Optimal Sensor Deployment for Value-Fusion Based Detection,” in GLOBECOM, 2009.
[18]. Z. Yuan, R. Tan, G. Xing, C. Lu, Y. Chen, and J. Wang, “Fast Sensor Deployment for Fusion-Based Target Detection,” in IEEE Real-Time Systems Symposium (RTSS’08), Dec. 2008.
[19]. Olariu S. and Stojmenovic I., “Design Guidelines for Maximizing Lifetime and Avoiding Energy Holes in Sensor Networks with Uniform Distribution and Uniform Reporting,” IEEE INFOCOM, 2006.
[20]. M. Cardei, Y. Yang, and Jie Wu, “Non-Uniform Sensor Deployment in Mobile Wireless Sensor Networks,” World of Wireless, Mobile and Multimedia Networks, 2008.
[21]. J. Zhang, S. Ci, H. Sharif, and M. Alahmad, “A Battery-Aware Deployment Scheme for Cooperative Wireless Sensor Networks,” in GLOBECOM, 2009.
[22]. T.S. Rappaport, “Wireless Communications: Principles and Practice,” New Jersey: Prentice Hall, 2002.
[23]. M. Hata, “Empirical Formula for Propagation Loss in Land Mobile Radio Service,” IEEE Trans. on Vehicular Technology, 29(3):317-325, Aug. 1980.