跳到主要內容

臺灣博碩士論文加值系統

(44.201.99.222) 您好!臺灣時間:2022/12/04 00:45
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:張鴻偉
研究生(外文):Chang, Hung-Wei
論文名稱:一個應用於存在障礙物之無線感測網路上的虛擬錨點繞徑協定
論文名稱(外文):A Virtual Anchor Routing Protocol for Wireless Sensor Networks with Obstacles
指導教授:黃志銘黃志銘引用關係
指導教授(外文):Huang, Jyh-Ming
口試委員:黃志銘陳烈武王壘
口試委員(外文):Huang, Jyh-MingChen, Lien-WuWang, Lei
口試日期:2017-06-22
學位類別:碩士
校院名稱:逢甲大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:中文
論文頁數:39
中文關鍵詞:無線感測網路虛擬錨點貪婪繞徑地域空洞
外文關鍵詞:wireless sensor networkslocal minimumgreedy algorithmvirtual anchor
相關次數:
  • 被引用被引用:0
  • 點閱點閱:65
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
貪婪繞徑(Greedy Routing)演算法是一種常見應用於無線感測網路(WSN)環
境中的地理繞徑協定,但卻容易因網路中的障礙物阻絕,或因節點配置不均而產
生的地域空洞(Void),致使資料封包傳輸失敗,或拉長了封包傳輸距離與傳輸延
遲時間。
本論文中,我們提出一個虛擬錨點繞徑協定,利用建構包圍障礙物或空洞的
虛擬圓,藉由來源節點及目的節點與其切線交點關係,找出虛擬錨點,並比較我
們所提出的兩種傳輸模式路徑長度,供來源節點判斷選擇最佳的傳輸路線,提前
繞過障礙物或空洞,以縮短傳輸距離與傳輸延遲時間。
為了驗證本論文所提的繞徑協定效益,我們利用C 程式語言來撰寫模擬程
式,並在模擬中設計了一些情況;其一,在感測環境中平均分佈節點,並於網路
中設置不同大小、形狀、數量的障礙物或空洞的情況下,以進行模擬比較,其二,
我們模擬現實無線網路的情況,於感測範圍中隨機分佈節點,針對因節點密度稀
疏、不均而隨機產生不同大小、形狀、數量的地域空洞,進行模擬比較。我們觀
察所提出的方法,對資料封包傳輸距離與傳輸延遲時間,以及資料封包進入虛擬
區域比率的影響(亦即資料封包靠近障礙物的機率),並與過去幾個相關文獻做比
較。模擬結果顯示,相較於過去幾個相關文獻GPSR、BHOP-GR 和BVR-VCM,
我們所提出的方法在平均傳輸距離上縮短了約5%~19%;在平均傳輸延遲時間改
善了約7%~17%;至於資料封包進入虛擬區域的比率則是約少了2%~17%。
誌 謝............................................................................................................................. i
摘 要............................................................................................................................ ii
目 錄............................................................................................................................ v
圖目錄........................................................................................................................... vi
第一章 研究背景與動機.............................................................................................. 1
第二章 目前相關研究.................................................................................................. 3
2.1 GPSR............................................................................................................. 3
2.2 BHOP-GR ..................................................................................................... 4
2.3 BVR-VCM .................................................................................................... 6
第三章 研究方法與步驟.............................................................................................. 9
3.1 虛擬圓及虛擬座標建構階段........................................................................ 9
3.2 資料封包傳輸階段...................................................................................... 10
3.2.1 虛擬錨點與虛擬圓座標傳輸模式.................................................... 11
3.2.2 虛擬錨點過度偏離問題之對策........................................................ 12
第四章 模擬比較與分析............................................................................................ 14
4.1 模擬環境與參數.......................................................................................... 14
4.2 不同大小單一障礙物之影響...................................................................... 14
4.3 多個相同大小障礙物之影響...................................................................... 19
4.4 各種節點密度之影響.................................................................................. 22
第五章 結論................................................................................................................ 27
參考文獻...................................................................................................................... 29
[1] Shih-Yeh Chen, Wei-Tsong Lee, Han-Chieh Chao, Yueh-Min Huang, and Chin-
Feng Lai, "Adaptive Reconstruction of Human Motion on Wireless Body Sensor
Networks," Wireless Communications and Signal Processing, pp. 1-5, 2011.
[2] Fuqiang Zou, Bo Yang, and Yitao Cao, "Traffic Light Control for a Single
Intersection Based on Wireless Sensor Network," Electronic Measurement &
Instruments, pp. 1040-1044, 2009.
[3] Mingxiao Lu; Xiaoguang Zhao; Yikun Huang,“Fast Localization for Emergency
Monitoring and Rescue in Disaster Scenarios Based on WSN,” 14th International
Conference on Control, Automation, Robotics and Vision (ICARCV), pp. 1–6,
2016.
[4] Chao Gui and Prasant Mohapatra, "Power Conservation and Quality of
Surveillance in Target Tracking Sensor Networks," Mobile Computing and
Networking, pp. 129-143, 2004.
[5] J. N. Al-Karaki and A. E. Kamal, “Routing Techniques in Wireless Sensor
Networks: A Survey,” IEEE Wireless Communications, vol. 11, issue. 6, pp. 6-28,
2004.
[6] M. Mauve, J. Widmer and H. Hartenstein, “A Survey on Position-based Routing
in Mobile Ad Hoc Networks,” IEEE Network Magazine, Vol. 15, No. 6, pp. 30–
39, 2001.
[7] S. Wan, Y. Zhang, “Coverage Hole Bypassing in Wireless Sensor Networks,”
12th International Conference on Mobile Ad-Hoc and Sensor Networks, pp. 409 -
411, 2016.
[8] S. M. Ghoreyshi, A. Shahrabi and T. Boutaleb, “An Underwater Routing Protocol
with Void Detection and Bypassing Capability,” IEEE 31st International
Conference on Advanced Information Networking and Applications, pp. 530 - 537,
2017.
[9] N. Ahmed, S. Kanhere, and S. Jha, “The Holes Problem in Wireless Sensor
Networks: A Survey,” ACM Sigmobile Mobile Computing and Communication
Review, Vol. 9, No. 2, pp. 4-18, 2005.
[10] B. Karp and H. T. Kung, “GPSR: Greedy Perimeter Stateless Routing for Wireless
Networks,” Proc. of the 6th annual international conference on Mobile computing
and networking, pp. 243-254, 2000.
[11] D. Zhang and E. Dong, “A Virtual Coordinate-based Bypassing Void Routing for
Wireless Sensor Networks,” IEEE Sensors J., vol. 15, no. 7, pp. 3853–3862, Jul.
2015.
[12] F. Li, B. Zhang, and J. Zhang, “Geographic Hole-bypassing Forwarding Protocol
for Wireless Sensor Networks,” IET Commun., vol. 5, no. 6, pp. 737–744, Apr.
2011..
[13] Z. Jiang, J. Ma, and W. Lou, “An Information Model for Geographic Greedy
Forwarding in Wireless Ad-hoc Sensor Networks,” in Proc. of IEEE INFOCOM,
2008.
[14] M. Choi and H. Choo. “Bypassing Hole Scheme Using Observer Packets for
Geographic Routing in WSNs,” In Proc. of Intl. Conf. on Information Networking,
ICOIN’11, pp. 435–440, 2011.
[15] Toussaint G. The Relative Neighborhood Graph of a Finite Planar Set. Pattern
Recognition, 1980, 12(4): 261-268.
[16] Gabriel K and Sokal R. A New Statistical Approach to Geographic Variation
analysis. Systematic Zoology, 1969, 18: 259-278
[17] B. H. Wellenhof, H. Lichtenegger, J. Collins, Global Positioning System: Theory
and Practice, fifth ed., Springer Verlag, 2001.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top