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系統識別號 U0002-2307201219501300
中文論文名稱 在行動感測網路中具不同權重值之資料收集機制
英文論文名稱 Weighted Targets Patrolling Mechanisms in Wireless Mobile 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 En
學年度 100
學期 2
出版年 101
研究生中文姓名 何怡蓉
研究生英文姓名 Yi-Jumg Ho
學號 699420096
學位類別 碩士
語文別 中文
第二語文別 英文
口試日期 2012-06-07
論文頁數 99頁
口試委員 指導教授-張志勇
指導教授-陳建彰
委員-陳宗禧
委員-陳裕賢
委員-洪麗玲
委員-張志勇
中文關鍵字 目標點覆蓋  行動收集器  資料收集  無線感測網路 
英文關鍵字 Target coverage  data mule  data collection  WSNs 
學科別分類 學科別應用科學資訊工程
中文摘要 目標物覆蓋(Target Coverage)問題在無線感測網路中一直受到廣泛的討論,本論文考慮監控場景中存在許多我們所感興趣的位置(Points of Interest ( POIs )),其分散於不連續的區域中,若以固定式感測器佈建整個網路,將佈建數量龐大的感測器,造成佈建成本昂貴,而收集資料時亦造成耗電量不均以及感測器不亦充電的問題。因此,本論文以具移動性之行動資料蒐集裝置(Data Mule)來達成網路的連通及目標物監控或資訊收集等目的。本論文首先提出了Time-Constrained Weighted Targets Patrolling (TCWTP) Algorithm,使分處於各地的Mobile Data Mules以分散式的方式,在POIs之間建置出有效率的巡邏路徑,進行感測及資料蒐集的任務。不同於以往的研究,本論文考慮所有POIs具有不同的權重值,Data Mule對於重要性較高的POIs,將給予其較高的感測與拜訪頻率,以提高其資料更新之速度‧此外,本論文亦針對Mobile Spatial Coverage的議題,考慮監控場景中存在許多不具感測與通訊能力的目標物(POIs),並解決前述目標物監控所遭遇的硬體成本、目標物監控品質以及Data mules電量等三大挑戰。
英文摘要 This thesis first considers the weighted target patrolling problem which asks a set of mobile data mules (DMs) to efficiently patrol a set of given weighted targets. A patrolling algorithm, called Time-Constrained Weighted Target Patrolling (TCWTP), is presented aiming to construct an efficient patrolling route for a number of given data mules such that targets with higher weights have higher visiting frequency and the overall visiting frequency is stable. Performance study demonstrates that the proposed algorithm outperforms existing approaches in terms of patrolling delay and quality of monitoring.
論文目次 目錄
圖目錄 V
表目錄 VII
第一章 Introduction 1
第二章 Related Work 5
第三章 TCWTP Algorithm 9
3.1 Network Environment and Problem Formulations 10
3.1.1 Network Model 10
3.1.2 Problem Formulations 11
3.2 Basic Concept 14
3.3 TCWTP Algorithm 18
3.3.1 Paths Construction Phase 18
3.3.2 Position Initialization 23
3.3.3 Speed Control Phase : Target Base Policy 32
3.4 Performance Study 38
3.4.1 Simulation Model 38
3.4.2 Performance Study 39
第四章 Data Mule Recharging Mechanism 51
4.1 Network Model and Problem formulations 52
4.1.1 Network Model 52
4.1.2 Problem Formulations 54
4.2 Basic Concept and Challenges 61
4.3 Algorithm 67
4.3.1 Location Initialization Phase 68
4.3.2 Path Construction Phase 69
4.3.3 System Stable Phase 69
4.3.4 Monitoring and Data Collection Phase 75
4.3.5 Data Mule State Diagram 83
4.4 Performance Study 87
4.4.1 Simulation Model 87
4.4.2 Performance Study 88
第五章 Conclusions 91
References 92
附錄—英文論文 96

圖目錄
圖(3.1) 網路環境 11
圖(3.2) Data Collection Network Environment 14
圖(3.3)(a) Weighted patrolling route H1 15
圖(3.3)(b) Weighted patrolling route H2 15
圖(3.4) Ideal Schedule for each target node 16
圖(3.5) Target Base Policy - Speed Control 17
圖(3.6) TCWTP Algorithm 18
圖(3.7) TCWTP Path Construction Algorithm 23
圖(3.8)(a) 迴路權重值(wiH)相等 25
圖(3.8)(b) 迴路長度( |Hi| )相等 25
圖(3.9) Initialization - Breaking Point 31
圖(3.10)(a) Respective frequency of target 33
圖(3.10)(b) Unstable frequency 34
圖(3.10)(c) Stable frequency 34
圖(3.11) 巡邏路徑切分速度調整路段 35
圖(3.12) Speed Control Phase 37
圖(3.13) 行動感測網路中目標物覆蓋演算法之AVI比較 40
圖(3.14) 行動感測網路中目標物每次被拜訪之AVI 41
圖(3.15)(a) 尚未進行速度控制機制在VIP數及權重值大小不同時之AVI比較 42
圖(3.15)(b) 速度控制機制在VIP數及權重值大小不同時之AVI比較 43
圖(3.16) 行動感測網路中目標物覆蓋演算法之SD比較 44
圖(3.17) 行動感測網路中目標物覆蓋演算法之SD比較 45
圖(3.18) 六大監控場景 46
圖(3.19) 六大監控場景所需的DMs個數比較 47
圖(3.20) 路徑毀損對目標物監控品質影響之比較 49
圖(3.21) POI被DMs拜訪之公平性比較 50
圖(4.1) 網路環境 53
圖(4.2) 所建置之資料回傳與充電路徑 61
圖(4.3) 目標物g3上DM電量狀態 65
圖(4.4) 目標物g4上DM電量狀態 65
圖(4.5) DM m4充電門檻值之電量示意圖 78
圖(4.6) DM電量狀態圖 83
圖(4.7) Energy Efficient Recharging Algorithm 86
圖(4.8) 充電機制中DMs的平均剩餘電量之觀察 89
圖(4.9) DM充電之成本效益 90

表目錄
表(3.1) 模擬參數 38
表(4.1) 問題描述之符號定義 55
表(4.2) 模擬參數 87
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