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系統識別號 U0002-0706201215020000
中文論文名稱 水下聲波網路中,具深度調節之繞徑協定研究
英文論文名稱 A Depth Adaptive Routing Protocol for Underwater Acoustic Sensor Networks
校院名稱 淡江大學
系所名稱(中) 資訊工程學系資訊網路與通訊碩士班
系所名稱(英) Master's Program in Networking and Communications, Department of Computer Science and Information Engineering
學年度 100
學期 2
出版年 101
研究生中文姓名 王清弘
研究生英文姓名 Ching-Hung Wang
學號 699420476
學位類別 碩士
語文別 英文
口試日期 2012-06-22
論文頁數 60頁
口試委員 指導教授-石貴平
委員-王三元
委員-廖文華
委員-陳彥達
委員-石貴平
中文關鍵字 聲速  水下感測網路  聲波通訊  繞徑 
英文關鍵字 Sound speed  Underwater sensor networks  Acoustic communication  Routing 
學科別分類 學科別應用科學資訊工程
中文摘要 在本篇論文中,我們將提出一個適用於水下無線聲波感測網路環境之繞徑協定。聲波傳輸速度在不同海水深度時將有所變化。在水下 1000 公尺時聲速最慢,1000 公尺以上及以下速度皆較快。利用此特性,本篇論文提出一個聲速與海水深度變化之數學模型,並藉由此模型建立繞徑表。傳送端節點可依據所在之深度不同,透過查表的方式,可選擇向上傳送、向下傳送或直接傳送的方式。在盡可能的縮短傳輸時間的情形下,將封包傳送至水面上目的端節點。
在模擬的部分,由實驗結果可知,本論文所提出之封包傳輸路徑,雖然較傳統最短傳輸路徑長,但花費的傳輸時間較傳統最短傳輸路徑少。同時,隨著傳輸範圍的增加,傳輸時間亦隨之減少。此實驗結果足以驗證本篇論文所提出的具深度調節之繞徑協定可善用聲速在水下深度不同傳輸速度隨之改變的特性,以減少封包傳輸之時間花費。
英文摘要 In this thesis, we propose a depth adaptive routing protocol named DARP for underwater acoustic sensor networks. Sound speed varies with water depth. As the depth of water is 1000 meters, the speed of acoustic wave is the slowest. Based on this observation, this proposal analyzes the impact of sound speed in different water depth and with various transmission distances and then the analysis results are formulated as a routing table. Therefore, each sender can refer to this routing table to transmit with a shortest end-to-end delay time in DARP.
The simulation results show that the routing path is longer than the traditional shortest path, but the cost time of our proposed methods is less than the traditional shortest path. It improve the property of the sound speed is change by the water depth. At the same time, the large the transmission range is, the less the time is.
論文目次 Contents
Contents III
List of Figures V
List of Tables VIII
1 Introduction 1
2 Preliminaries 5
3 Forwarding Path Analysis 9
3.1 Numerical Analyses 9
3.2 End-to-End Delay Estimation of Downward Path 16
3.3 End-to-End Delay Estimation of Straight Path 17
3.4 End-to-End Delay Estimation of Upward Path 19
4 The Depth Adaptive Routing Protocol (DARP) 21
4.1 Construction the Routing Table 21
4.2 Calculation the Waiting Time 30
4.3 Local minimum Problem 31
4.4 The DARP Algorithm 35
5 Performance Evaluations 36
5.1 The relationship between the end-to-end delay and the depth of source 37
5.2 The relationship between the end-to-end delay and the width 38
5.3 The relationship between the path length and the width 41
5.4 The relationship between the end-to-end delay and the packet size 44
5.5 The relationship between the end-to-end delay and the transmission ranges 44
6 Conclusions 48
Bibliography 50
Appendix 54

List of Figures
Figure 1.1 A scenario of UASNs 2
Figure 2.1 Changes in speed of sound by depth 6
Figure 3.1 Upward, straight, and downward path in the network 10
Figure 3.2 The downward path with the sinking, horizontal, and floating phases 11
Figure 3.3 Four considered paths in the numerical evaluation 11
Figure 3.4 Comparisons of the end-to-end delay of the straight, upward, and downward paths in terms of the depth of the source (d) 12
Figure 3.5 Comparisons of the end-to-end delay of the straight, upward, and downward paths in terms of the width (w) 13
Figure 3.6 The downward path changed by the major parameters θ1 and θ2 16
Figure 3.7 The straight path changed by the major parameter θ 18
Figure 3.8 The upward path changed by the major parameter θ 19
Figure 4.1 The end-to-end delay in terms of different depths of source when w=10km 22
Figure 4.2 The end-to-end delay in terms of different depths of source when w=20km 23
Figure 4.3 The end-to-end delay in terms of different depths of source when w=30km 23
Figure 4.4 The end-to-end delay in terms of different depths of source when w=40km 24
Figure 4.5 The end-to-end delay in terms of different depths of source when w=50km 24
Figure 4.6 The end-to-end delay in terms of different depths of source when w=60km 25
Figure 4.7 The end-to-end delay in terms of different depths of source when w=70km 25
Figure 4.8 The end-to-end delay in terms of different depths of source when w=80km 26
Figure 4.9 The end-to-end delay in terms of different depths of source when w=90km 26
Figure 4.10 The end-to-end delay in terms of different depths of source when w=100km 27
Figure 4.11 The end-to-end delay in terms of different depths of source when w=150km 27
Figure 4.12 The end-to-end delay in terms of different depths of source when w=200km 29
Figure 4.13 The illustration of parameters in the waiting function 30
Figure 4.14 Local minimum phenomenon 32
Figure 4.15 The illustration of bypassing the hole 33
Figure 4.16 The illustration of the retransmission 33
Figure 5.1 The end-to-end delay in terms of different depths of source when w=10km 38
Figure 5.2 The end-to-end delay in terms of different depths of source when w=50km 39
Figure 5.3 The end-to-end delay in terms of different depths of source when w=100km 39
Figure 5.4 The end-to-end delay in terms of different depths of source when w=150km 40
Figure 5.5 The end-to-end delay in terms of different depths of source when w=200km 40
Figure 5.6 The end-to-end delay in terms of different widths when d=4500m 41
Figure 5.7 The end-to-end delay in terms of different widths when d=8000m 42
Figure 5.8 The path length in terms of different widths when d=4500m 43
Figure 5.9 The path length in terms of different widths when d=8000m 43
Figure 5.10 The end-to-end delay in terms of different packet sizes when d=3000m and w=100km 45
Figure 5.11 The end-to-end delay in terms of different packet sizes when d=3000m and w=200km 45
Figure 5.12 The end-to-end delay in terms of different transmission ranges when d=3000m and w=100km 46
Figure 5.13 The end-to-end delay in terms of different transmission ranges when d=3000m and w=200km 47

List of Tables
Table 4.1 The routing table in terms of different depths(d) of source and different width(w) of scenario(km) 28
Table 5.1 The simulation parameters 36
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