車載隨意行動網路(VANET)通訊最近已成為在無線網路領域，以及在汽車工業日益流行的研究議題。VANET研究的目標是開發一個車載通訊系統，能快速且具成本效益的達到資料散佈，用於改善乘客的安全性和舒適性。在模擬車載網路中最重要的參數之一是節點移動性，使用一個逼真的移動模型是重要的，它可以從模擬結果中正確的反映出真實世界的VANET效能。為了研究在VANET中的效能，我們延伸了車載網路移動模型產生器(MOVE)，增加了互動式的模擬(如重新路徑選擇的應用)、逼真的無線電模型(Radio model)、與使用機率模型於目的地選擇產生器。我們觀察到移動模型的細節影響了VANET的效能，這結果也顯示在移動模型中選擇一個適當的細節水平，對VANET的模擬是重要的。
從研究結果得知節點移動性在車載網路中是強烈地受到駕駛員的行為影響，它可以在不同層面上改變道路交通。例如，駕駛員在路徑和目的地選擇的偏好會進一步影響整個在網路的拓撲結構。因此，為了了解網路拓撲對於VANET效能的影響，我們展示四個例子對於偏好路線的影響：在十字路口轉彎的決策、選擇最快路徑與最短路徑、決策繞路當遇到堵車時、與目的地選擇模型。我們還討論了不同目的地選擇模型如何影響兩個實際智慧型交通系統(ITS)的應用：交通流量監控和事件廣播。我們觀察到當駕駛員的路徑選擇中使用最短路徑網路效能普遍會比較好，相較於使用最快路徑的情形時。我們指出了一個目的地選擇模型對於不同ITS的應用有不同的影響。此外，我們觀察到模擬結果在不同節點密度設定下沒有顯著的影響，當車輛選擇其目的地以Pareto分佈時。最後，我們發現了多數節點可能會聚集於地圖的中心，當目的地選擇模型使用uniform分佈時。
最後，鑑於有些車輛可能沒有網路功能加入車載網路或存取網際網路，我們提出一個合作式頻寬分享協定(CBSP)，它建立於多路徑傳輸控制協定(MPTCP)之上讓車輛可以從它的鄰近節點買頻寬。CBSP使用虛擬介面(Virtual interface)彈性的管理智慧型手機上的介面，以對應每個協助者(Helper)。然而，目前MPTCP封包排程的實作方式會衍生下述兩個問題，當封包排程器(Packet scheduler)同時考量封包往返時間(RTT)與可用的壅塞窗口(cwnd)來分派封包時(稱為RTT scheduling)。(1) 失序封包(Out-of-order packets)：封包可能因有限的cwnd送至較慢的路徑，導致out-of-order packets的數量增加。(2) 偏頗排程(Biased-feeding)：Packet scheduler會先用盡當前排程中的子網路流(subflow)全部的cwnd，封包才會分派到下一個subflow。CBSP使用virtual interfaces結合MPTCP的subflows已避免實作上MPTCP的修改，並彈性管理智慧型手機的網路介面於每個helper。我們使用Scheduled window-based transmission control (SWTC)排程演算法來改善在MPTCP中的封包排程的效能。結果顯示SWTC可以有效的減少out-of-order packets數量與得到較高的利用率於RTT scheduling在不同的網路異質性下與避免biased-feeding的發生。

Vehicular Ad-Hoc Network (VANET) communication has recently become an increasingly popular research topic in the area of wireless networking, as well as in the automotive industry. The goal of VANET research is to develop a vehicular communication system to enable the quick and cost-efficient distribution of data for the benefit of passengers’ safety and comfort. One of the most important parameters in simulating vehicular networks is the node mobility. It is important to use a realistic mobility model so that results from the simulation correctly reflect the real-world performance of a VANET. The previous version of the MObility model generator for VEhicular networks (MOVE) did not support interactive simulations, nor allow realistic vehicular network simulations that considered a radio model, and users could also not rapidly generate a mobility trace with specific probability distributions for the destination selection of each car (meaning that each car needs to be added individually). We thus extend MOVE by adding interactive simulations via the Traffic Control Interface (TraCI) in order to carry out rerouting to reduce travel time, provide realistic radio models, and enable destination selection under various probability distributions. We observe the effects of the various details of the resulting mobility models on the performance of VANET, and show that selecting an appropriate level of detail in the mobility model is important with regard to the performance of the VANET simulation.
The results of this work show that node mobility in a vehicular network is strongly affected by the drivers’ behavior, which can change road traffic at different levels. For example, drivers’ preferences with regard to path and destination selection can affect the overall network topology. Therefore, in order to understand the effect of network topology on VANET performance, we examine the effects of preferred routes using four examples: turning decisions at an intersection, choice between fastest and shortest paths, decision to re-route when encountering traffic jam, and destination selection. We also discuss how different destination selection models affect two practical intelligent transport system (ITS) application scenarios: traffic monitoring and event broadcasting. We observe that the network performance is generally better when one model’s drivers’ choose routes using the shortest path model, as compared to using the fastest path model. We show that a destination selection model can have different effects for different ITS applications. Furthermore, we observe that simulation results are not significantly affected by different node density settings when cars pick their destination following a Pareto distribution. Finally, we show that more nodes might concentrate at the center of the map when the uniform distribution is chosen to model the destination selection.
Finally, given that some cars might not have the networking capability to join the vehicular network or access the Internet, we propose a collaborative bandwidth sharing protocol (CBSP) built on top of MultiPath TCP (MPTCP), as this allows multihoming to enable users to buy bandwidth on demand from neighbors (called helpers). Although MPTCP provides required multihoming functionality, the current implementation of packet scheduling in MPTCP leads to the following two problems when the packet scheduler considers both round trip time (RTT) and available congestion window (cwnd) to dispatch packets (called RTT scheduling in this thesis). (1) Out-of-order packets: packets might be sent to slower links due to limited cwnd, thus increasing the number of out-of-order packets. (2) Biased-feeding: the fastest link might always be selected to send packets whenever it has available cwnd, while other links are only selected when the fastest link has no available cwnd. CBSP uses virtual interfaces to bind the subflows of MPTCP to avoid modifying the implementation of MPTCP, and to flexibly manage the interfaces of smartphones for each helper. We employ the Scheduled Window-based Transmission Control (SWTC) scheduling algorithm to improve the performance of packet scheduling in MPTCP. The results show that SWTC can more efficiently reduce the number of out-of-order packets than RTT scheduling under various network heterogeneities, and also avoid biased-feeding.

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