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研究生: 張伊姍
Yi-Shan Chang
論文名稱: 用於大規模無線感測網路之叢集化暨繞送設計
Design of Routing and Clustering for a Large-Scale Wireless Sensor Network
指導教授: 馮輝文
Huei-Wen Ferng
口試委員: 林嘉慶
張宏慶
范欽雄
學位類別: 碩士
Master
系所名稱: 電資學院 - 資訊工程系
Department of Computer Science and Information Engineering
論文出版年: 2018
畢業學年度: 106
語文別: 中文
論文頁數: 49
中文關鍵詞: 大規模無線感測網路叢集化繞送叢集大小負擔平衡
外文關鍵詞: Large-Scale WSN
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  • 無線感測網路環境能根據不同領域的特性收集需要的資料,為了部署環境設備的方便性,多數選擇使用有限能源的感測節點,因此,如何發揮能源最大效益以獲得最佳網路壽命便為一項受到關注的議題。叢集化為最常被使用的方法之一,另一則是繞送機制,因此,我們研究如何兼具叢集化及繞送機制,以達最佳效果。我們提出的演算法當中,除了能夠將感測節點傳送端及接收端之間的距離限制在耗電較少的傳送範圍內之外,還能夠維持節點之間連接的強健性。此外,我們亦挑選出輔助感測節點(Assistive Sensor Node) 之集合來規劃靠近匯集點(Sink)區域的封包繞送,不僅如此,本研究方法增加叢集之間成員個數的平衡機制,達成負擔平衡的優點。透過模擬方式,我們驗證所提演算法不僅提升了整體網路壽命,繞送機制的強健性也可獲得加強。


    Wireless Sensor Networks (WSNs) can collect data according to the natures of different fields. For convenience of deployment, energy limited sensor nodes are usually selected. It is a challenging issue to prolong the network lifetime in a WSN. Clustering is a popular approach to address such an issue. On the other hand, routing protocols are also important touch this issue. Therefore, we shall propose a mechanism considering both clustering and routing protocol to maximize the network lifetime. As far as routing is concerned, sensor nodes are allowed to transmit data in the transmission range with minimum energy consumption. Besides, robust connectivity between sensors nodes is further enhanced. Furthermore, a set containing assistive sensor nodes (ASNs) is provided in the environment for bettering routing around the sink to avoid the energy hole problem. Last but not least, how to balance cluster sizes to achieve load balance is further considered in our mechanism. Via simulations, we successfully show that a longer network lifetime and better robustness in routing are achieved by our proposed mechanism as compared to the closely related mechanism in the literature.

    目錄 論文指導教授推薦書. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i 考試委員審定書. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii 中文摘要. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii 英文摘要. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv 誌謝. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v 目錄. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi 表目錄. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii 圖目錄. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix 第一章、緒論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 大規模無線感測網路之簡介. . . . . . . . . . . . . . . . . . . . . . . 1 1.2 叢集化之簡介. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.3 研究動機與目的. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.4 論文其他章節安排. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 第二章、相關文獻探討. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1 LEACH 演算法. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 平均叢集大小. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.3 RMER 演算法. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.4 MLCMS 演算法. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.5 JCR 演算法. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.5.1 節點特性. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.5.2 節點狀態. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.5.3 演算法分析. . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 第三章、系統模型. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.1 網路模型. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.2 能源耗損模型. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.3 資料聚合模型. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 第四章、所提方法之規劃與設計. . . . . . . . . . . . . . . . . . . . . . . . . . 17 4.1 環境梯度設置. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 4.2 挑選輔助感測節點集合. . . . . . . . . . . . . . . . . . . . . . . . . . 20 4.3 選定叢集頭之策略. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 4.4 輔助感測節點負責之匹配機制. . . . . . . . . . . . . . . . . . . . . . 24 4.5 叢集成員個數平衡機制. . . . . . . . . . . . . . . . . . . . . . . . . . 26 第五章、數值結果與討論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 5.1 模擬環境參數設定. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 5.2 網路壽命. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 5.3 叢集頭個數. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 5.4 孤立點叢集比率. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 5.5 所有叢集成員個數的變異係數. . . . . . . . . . . . . . . . . . . . . . 34 第六章、結論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 參考文獻. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

    [1] L. Chen, D. Yang, Z. Xu, and C. Chen, “An adaptive routing strategy for clusterbased
    wireless sensor networks,” in Proc. Chinese Control and Decision Conference
    (CCDC), pp. 5224–5229, May. 2015.
    [2] H.-W. Ferng, R. Tendean, and A. Kurniawan, “Energy-efficient routing protocol for
    wireless sensor networks with static clustering and dynamic structure,” vol. 65, no. 2,
    Jul. 2012, pp. 347–367.
    [3] W. B. Heinzelman, A. P. Chandrakasan, and H. Balakrishnan, “An applicationspecific
    protocol architecture for wireless microsensor networks,” IEEE Transactions
    on Wireless Communications, vol. 1, no. 4, pp. 660–670, Oct. 2002.
    [4] O. Younis and S. Fahmy, “HEED: a hybrid, energy-efficient, distributed clustering
    approach for ad hoc sensor networks,” IEEE Transactions on Mobile Computing,
    vol. 3, no. 4, pp. 366–379, Oct. 2004.
    [5] F. Ye, G. Zhong, S. Lu, and L. Zhang, “Gradient broadcast: A robust data delivery
    protocol for large scale sensor networks,” Wirel. Netw., vol. 11, no. 3, pp. 285–298,
    May 2005.
    [6] S. C. Ergen and P. Varaiya, “TDMA scheduling algorithms for wireless sensor networks,”
    Wireless Networks, vol. 16, no. 4, pp. 985–997, May 2010.
    [7] S. Fang, S. M. Berber, and A. K. Swain, “An overhead free clustering algorithm for
    wireless sensor networks,” in Proc. IEEE Global Telecommunications Conference
    GLOBECOM, Nov. 2007, pp. 1144–1148.
    [8] A. Riker, E. Cerqueira, M. Curado, and E. Monteiro, “A two-tier adaptive data aggregation
    approach for M2M group-communication,” IEEE Sensors Journal, vol. 16,
    no. 3, pp. 823–835, Feb. 2016.
    [9] N.-T. Nguyen, B.-H. Liu, V.-T. Pham, and Y.-S. Luo, “On maximizing the lifetime for
    data aggregation in wireless sensor networks using virtual data aggregation trees,”
    Computer Networks, vol. 105, pp. 99 – 110, Aug. 2016.
    [10] T. Qiu, X. Liu, L. Feng, Y. Zhou, and K. Zheng, “An efficient tree-based selforganizing
    protocol for internet of things,” IEEE Access, vol. 4, no. 6, pp. 3535–
    3546, Aug. 2016.
    [11] S. Hussain and O. Islam, “An energy efficient spanning tree based multi-hop routing
    in wireless sensor networks,” in Proc. IEEE Wireless Communications and Networking
    Conference (WCNC), March 2007, pp. 4383–4388.
    [12] R. S. Elhabyan and M. C. E. Yagoub, “Weighted tree based routing and clustering
    protocol for WSN,” in Proc. IEEE Canadian Conference on Electrical and Computer
    Engineering (CCECE), May 2013, pp. 1–6.
    [13] Z. Xu, C. Long, C. Chen, and X. Guan, “Hybrid clustering and routing strategy
    with low overhead for wireless sensor networks,” in in Proc. IEEE International
    Conference on Communications (ICC), May 2010, pp. 1–5.
    [14] S. Sasirekha and S. Swamynathan, “Cluster-chain mobile agent routing algorithm for
    efficient data aggregation in wireless sensor network,” Journal of Communications
    and Networks, vol. 19, no. 4, pp. 392–401, Aug. 2017.
    [15] V. Pal, G. Singh, and R. P. Yadav, “Balanced cluster size solution to extend lifetime
    of wireless sensor networks,” IEEE Internet of Things Journal, vol. 2, no. 5, pp.
    399–401, Oct. 2015.
    [16] M. Dong, K. Ota, and A. Liu, “RMER: Reliable and energy-efficient data collection
    for large-scale wireless sensor networks,” IEEE Internet of Things Journal, vol. 3,
    no. 4, pp. 511–519, Aug. 2016.
    [17] K. V. P. Kumar, M. K. Banga, V. U. Rani, B. M. Thippeswamy, and K. R. Venugopal,
    “EBDRA: Energy balanced dynamic cluster routing approach for WSN,” in
    Proc. IEEE International Conference on Recent Trends in Electronics, Information
    Communication Technology (RTEICT), May. 2016, pp. 141–145.
    [18] M. Soltani, M. Hempel, and H. Sharif, “Data fusion utilization for optimizing largescale
    wireless sensor networks,” in Proc. IEEE International Conference on Communications
    (ICC), June 2014, pp. 367–372.
    [19] K. L. Ang, J. K. P. Seng, and A. M. Zungeru, “Optimizing energy consumption for
    big data collection in large-scale wireless sensor networks with mobile collectors,”
    IEEE Systems Journal, vol. 12, no. 1, pp. 616–626, March 2018.
    [20] W. Twayej, H. S. Al-Raweshidy, M. Khan, and S. El-Geder, “Energy-efficient M2M
    routing protocol based on Tiny-SDCWN with 6LoWPAN,” in Proc. Computer Science
    and Electronic Engineering (CEEC), Sept. 2016, pp. 198–203.
    [21] Z. Xu, L. Chen, C. Chen, and X. Guan, “Joint clustering and routing design for
    reliable and efficient data collection in large-scale wireless sensor networks,” IEEE
    Internet of Things Journal, vol. 3, no. 4, pp. 520–532, Aug. 2016.

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