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研究生: 陳偉華
Wei-hua Chen
論文名稱: 無線感測網路中之共同移動節點偵測
Virtual Coordinate Based Co-moving Detection in Wireless Sensor Networks
指導教授: 張貴雲
Guey-yun Chang
口試委員:
學位類別: 碩士
Master
系所名稱: 資訊電機學院 - 資訊工程學系
Department of Computer Science & Information Engineering
畢業學年度: 99
語文別: 英文
論文頁數: 27
中文關鍵詞: 共同移動無線感測網路
外文關鍵詞: Wireless sensor networks, co-moving
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  • 在行動無線感測網路中,了解節點的移動模式是很重要的。有許多應用需要節點及附近的節點一起協作來完成,例如以資料為中心的應用。許多社交工程的研究或是野生動物觀察與追蹤也需要知道許多個體與個體間的互動情形。因此,了解節點間的互動模式是很重要的。在這篇論文中,我們提出一個基於虛擬座標的共同移動節點偵測方法。我們使用最大獨立集合的幾何特性來發展我們的虛擬座標系統。建立這樣的座標系統耗費成本很低並且相對準確,我們建立一個類似極座標的系統,只需一些坐標旋轉及可使虛擬座標與真實做標相符合。我們藉由虛擬座標的幫助來進行共同移動節點偵測。一套制定良好的比較規則能精準地判斷共同移動的節點。使用這種方法不需要精確的定位技術因此我們的方法是非常有效率的。


    In mobile wireless sensor networks, it is important to understand the moving pattern of sensor nodes. There are a lot of application that need sensors nearby to co-work, such as data centric applications. Thus, knowing the co-moving nodes will be helpful to these applications. In this thesis, we propose a co-moving sensor nodes detection mechanism based on virtual coordinate system. We use the geometric property of independent set to build our virtual coordinate system. The cost of building a virtual coordinate in this way is low and the result is relative accurate – just a coordinate rotation will it matches true coordinates. With the aids of virtual coordinate system, we can find out co-moving sensor node pairs efficiently since no precise localization scheme needed in our works. A well-defined comparison rule is used for co-moving detection.

    Chapter 1 Introduction………………………………………………..1 Chapter 2 Preliminaries………………………………………………4 2.1 Related Works…………………………………………………...4 2.2 Assumptions………………………………………………...7 Chapter 3 Virtual Coordinate based Co-moving Detection Scheme.8 3.1 Overview…………………………….………………………...8 3.2 Coordinate Assignment Phase…….…….………………………..10 3.2.1 Independent Set Discovery……………….……………………...10 3.2.2 Location Constant Assignment...……….……………………...12 3.3 Co-moving Detection Phase….………….…..…………………15 Chapter 4 Performance Evaluation………………………………19 4.1 Result of Virtual Coordinate based Co-moving Detection…………19 4.2 Network Density and Packet Amount……………………………21 4.3 Mobile Node Speed and Packet Amount………………………23 Chapter 5 Conclusions……………………………………………25 References……………………………………………………………26

    [1] Gayathri Chandrasekaran, Mesut Ali Ergin, Marco Gruteser,Richard P. Martin, Jie Yang, and Yingying Chen, “DECODE: Exploiting Shadow Fading to DEtect COMoving Wireless Devices,” IEEE Transactions on Mobile Computing , vol. 8, no. 7, pp.1663-1674, 2009.
    [2] Scott C.-H. Huang, Peng-Jun Wan, Chinh T. Vu, Yingshu Li and Frances Yao, “Nearly Constant Approximation for Data Aggregation Scheduling in Wireless Sensor Networks,” in Proc. of IEEE INFOCOM, 2007.
    [3] S. Ratnasamy, B. Karp, L. Yin, F. Yu, D. Estrin, R. Govindan, and S. Shenker, “GHT: A Geographic Hash Table for Data-Centric Storage,” in Proc. of ACM WSNA, 2002.
    [4] Caruso A., Chessa S., De S. and Urpi A. “GPS Free Coordinate Assignment and Routing in Wireless Sensor Networks,” in Proc. of IEEE INFOCOM, 2005.
    [5] M.J.Tsai, H.Y.Yang, and W. Huang, “Axis-based virtual coordinate assignment protocol and delivery-guaranteed routing protocol in wireless sensor networks,” in Proc. of IEEE INFOCOM, 2007.
    [6] Ben Leong, Barbara Liskov and Robert Morris “Greedy Vrtual Coordinates for Geographc Routing,” in Proc. of IEEE ICNP, 2007.
    [7] T. Watteyne, I. Auge-Blum, M. Dohler and Stephane Ubeda, “Dominique Barthel, Centroid virtual coordinates - A novel near-shortest path routing paradigm,” Computer Networks, vol. 53, no. 10, 2009.
    [8] Maximum independent at http://en.wikipedia.org/wiki/Maximum_independent_ set
    [9] Ananth Rao, Sylvia Ratnasamy, Christos Papadimitriou, Scott Shenker and Ion Stoica, “Geographic routing without location information,” in Proc. of ACM MOBICOM, 2003.
    [10] I. F. Akyildiz, W. Su, , Y. Sankarasubramaniam and E. Cayirci, “Wireless sensor networks: a survey,” Computer Networks, vol. 38, no. 4, 2002.
    [11] Ziguo Zhong, Ting Zhu, Dan Wang and Tian He; “Tracking with Unreliable Node Sequences,” in Proc. IEEE INFOCOM, 2009.
    [12] Chih-Yu Lin, Wen-Chih Peng and Yu-Chee Tseng, “Efficient in-network moving object tracking in wireless sensor networks,” IEEE Transactions on Mobile Computing , vol. 5, no. 8, 2006.
    [13] Hua-Wen Tsai1 Chih-Ping Chu and Tzung-Shi Chen, “Mobile object tracking in wireless sensor networks,” Computer Communications, vol. 30, no. 8, 2007.
    [14] Mirco Musolesi, Stephen Hailes and Cecilia Mascolo, “An Ad Hoc Mobility Model Founded on Social Network Theory,” in Proc. ACM/IEEE MSWiM, 2004.
    [15] Elizabeth M. Daly and Mads Haahr, “Social Network Analysis for Information Flow in Disconnected Delay-Tolerant MANETs,” IEEE Transactions on Mobile Computing, vol. 8, no. 5, 2009.
    [16] Wenbo He, Ying Huangt, Klara Nahrstedt and BoWu, “Message Propagation in Ad-Hoe-Based Proximity Mobile Social Networks,” in Proc. of IEEE PERCOM, 2010.
    [17] K. Muthukrishnan, M. Lijding, N. Meratnia, and P. Havinga, “Sensing motion using spectral and spatial analysis of wlan rssi,” in Proc. of EuroSSC, 2007.
    [18] T. Sohn, A. Varshavsky, A. LaMarca, M. Y. Chen, T. Choudhury, I. Smith, S. Consolvo, J. Hightower, W. G. Griswold, and E. de Lara, “Mobility detection using everyday gsm traces,” in Proc. of IEEE/IFIP UbiComp, 2006.
    [19] J. Krumm and E. Horvitz, “Locadio: inferring motion and location from wi-fi signal strengths,” in Proc. of MOBIQUITOUS, 2004.
    [20] G. Chandrasekaran, M. Ergin, M. Gruteser, R. Martin, J. Yang, and Y. Chen, “Decode: Detecting co-moving wireless devices,” in Proc. of MASS, 2008.
    [21] NS2 at http://www.isi.edu/nsnam/ns/
    [22] NSG at http://sites.google.com/site/pengjungwu/nsg

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