本論文研究車載隨意網路上的緊急訊息散佈。有關目前車載隨意網路的國際標準為802.11p，然而802.11p對於如何散佈緊急訊息完全沒有任何描述。對於這個問題，最簡單的方法是flooding，然而此法會引發廣播風暴的問題。另一種作法是車載隨意網路裡頭的車輛平時維護cluster（叢集）架構；一旦發生交通事故，cluster head指派離它最遠的cluster member來轉發此一緊急訊息。然而車載隨意網路的拓樸（topology）經常在改變，維護cluster結構需耗費可觀的頻寬，而緊急事故卻不常發生。為此我們提出新的緊急訊息任播（anycast）技術，稱為TSDA，不但能和802.11p共存，而且在所有車輛都不需發送beacon的情況下，僅需事先知道車輛密度的範圍，便能估算競爭參與緊急訊息轉播的車輛數目，以便很快地將緊急訊息散佈出去。模擬實驗結果顯示，就average one-hop delay、average message progress、message dissemination speed來說，TSDA勝過目前已知的3P3B緊急訊息任播協定。

In this thesis, we study how the vehicles that witness or sense the accidents can quickly disseminate emergency messages in a vehicular ad hoc network (VANET). The current international medium access control (MAC) standard for VANETs is IEEE 802.11p, which did not address this issue. The simplest way to disseminate emergency messages is flooding, which easily induces the broadcast storm problem, thus severely wasting bandwidth. An alternative way is to maintain clusters in a VANET. Then when an accident occurs, the cluster head near to that place can ask its farthest member to relay the emergency message. However, such an approach requires high overhead to constantly maintain cluster structure, while accidents rarely occur. Therefore, we design a new emergency message anycast protocol, named TSDA, in which the witness vehicle can quickly disseminate emergency messages by estimating the number of its neighbors even all vehicles do not broadcast beacons. More importantly, TSDA can coexist with 802.11p. Simulation results show that TSDA outperforms the existing 3P3B protocol in terms of average one-hop delay, average message progress, and message dissemination speed.

論文審定書 i
誌謝 ii
摘要 iii
Abstract iv
目錄 v
圖次 vii
表次 ix
第一章 緒論 1
1.1 動機與目標 1
1.2 相關文獻 2
第二章 TSDA協定 7
2.1 Witness Contention Procedure 7
2.2 Segment Selection Procedure 9
2.3 Relay Selection Procedure 10
第三章 效能分析與最佳化 13
3.1 Witness Contention Period的期望值 14
3.2 Segment Selection Period的期望值 16
3.3 Relay Selection Period的平均時間 18
3.4 One-Hop Message Progress 20
3.5 Message Dissemination Speed 21
3.6 Optimization of Segment Selection Procedure 21
3.7 Adaptive Tree-Splitting 23
第四章 模擬實驗 28
4.1 實驗環境及參數設定 28
4.2 模擬器設計與實作 30
4.3 模擬實驗結果 32
4.3.1 理論效能分析之驗證 33
4.3.2 不同密度下最佳方塊數量 36
4.3.3 估計誤差 38
4.3.4 TSDA-ASAT最佳的切方塊數量與回合數 40
4.3.5 車輛密度變化對效能的影響 42
4.3.6 車輛速度變化對效能的影響 45
4.3.7 Best effort data對於效能的影響 48
第五章 結論 52
參考文獻 53

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