[[alternative]]水下聲波網路中, 具深度調節之繞徑協定研究

碩士[[abstract]]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。[[abstract]]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.[[tableofcontents]]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[[note]]學號: 699420476, 學年度: 10