臺灣博碩士論文加值系統

車載無線隨意網路 (VANETs) 允許車輛在沒有固定網路設施的環境中互相傳送資料。而因為車輛移動迅速和隨時容易斷線的特性，在車載無線隨意網路中藉由經過多個節點來傳送資料是非常不穩定的。在都市的環境下，因為無線電訊號會被建築物阻礙的緣故，路由的問題又更為複雜。許多的研究已發表出，基於位置的路由協定在車載無線隨意網路中具有比較高的適應性，但是它們仍然具有一些缺點，像是在車輛改變方向時有較長的延遲時間。為了解決這個問題，我們提出了一個具有多重路徑且於位置的路由協定。多重路徑的路由方式可以增加連線的穩定度，並且對於偵測車輛的行進具有幫助。而且在我們的方法中，路徑的選擇方式和調整路徑的方法都是特別適用於都市環境的車載無線隨意網路之下。我們的網路模擬使用格子狀的架構來簡化都市的環境。實驗結果顯示出我們提出的協定在實驗環境中，對於平均的延遲時間和平均的傳送成功比例上具有較顯著的效能。

Vehicular ad hoc networks (VANETs) allow vehicles to transmit data to each other without fixed infrastructure. Multi-hop data delivery through VANETs is very unstable because of the factor of highly mobile and frequently disconnection. In a city scenario, routing problem is even more complicated because of the obstruction to the wireless radio by many buildings. Some research presents the position-based routing protocols have better adaptability in VANETs, but there are still some drawbacks, like the longer delay when the vehicle changes its direction. To address this issue, we propose a position-based routing protocol with multi-path routes. Multi-path routing increases the link stability and beneficial for detecting the movement of the vehicle. Moreover, the path selection and adjustment of our approach are adapted for the movement of vehicles in the city environment. Our simulation takes the grid structure to simplify the actual city environment. Experimental results show that our proposed protocol gets performance in average delay and average delivery ratio in the simulation environment.

1 Introduction 1
2 Related Work 5
2.1 Routing in MANETs 5
2.2 Routing in VANETs 6
2.3 Multi-path routing 9
3 Moving Direction Aware Routing 12
3.1 Destination location and path discovery 13
3.2 Path selection strategy and direction computation 16
3.2.1 Multiple path selection 16
3.2.2 Computation of path directions 19
3.2.3 Constraints of propagating route requests 21
3.3 Packet forwarding 21
3.4 Route maintenance 22
3.4.1 Temporary disconnection 23
3.4.2 Movement of the destination 24
3.4.3 Movement of the source 26
4 Simulation 28
4.1 Simulation environments 28
4.2 Simulation metrics 31
4.3 Simulation results 32
5 Conclusion 38
References 41

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