| 研究生: |
吳宗祐 Wu, Zhong-You |
|---|---|
| 論文名稱: |
運用行動邊緣計算架構下之802.11p車載網路的V2V2I車載資料分流機制 The Mobile Edge Computing (MEC)-based Vehicle-to-Vehicle-to-Infrastructure (V2V2I) VANET Data Offloading from the cellular network to the 802.11p Network |
| 指導教授: |
黃崇明
Huang, Chung-Ming |
| 學位類別: |
碩士 Master |
| 系所名稱: |
電機資訊學院 - 資訊工程學系 Department of Computer Science and Information Engineering |
| 論文出版年: | 2018 |
| 畢業學年度: | 107 |
| 語文別: | 英文 |
| 論文頁數: | 76 |
| 中文關鍵詞: | 車載資料分流 、行動邊緣計算 、路邊單位 、車對車 、車對基礎網路 、車對車對基礎網路通訊 |
| 外文關鍵詞: | VANET Data Offloading, Mobile Edge Computing, Road Side Unit (RSU), Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), Vehicle-to-Vehicle-to-Infrastructure (V2V2I) |
| 相關次數: | 點閱:85 下載:1 |
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本篇論文提出了基於行動邊緣計算架構下距離RSU n-hop 的車對車對基礎網路分流機制。假設一輛車V透過4G/5G行動網路與網路上的節點PX進行通訊而在,只能透過行動網路的方式與網路上的節點互相通訊,此時V的前方有一個IEEE 802.11p RSU,在V尚未進入此RSU的通訊範圍內時,若能建立一條n-hop 的車對車分流路徑,使V能透過n-hop 的車對車的車間通訊與前方的RSU進行通訊,則完成車對車對基礎網路的分流機制。另一方面,若V離開了RSU的通訊範圍,若此時能建立一條 n-hop 的車對車分流路徑,使V能透過n-hop 的車對車的車間通訊與後方的RSU進行通訊,則這輛車能夠繼續使用車載網路進行分流。本篇論文提出了以行動邊緣計算為基礎的方法來解決車載網路車對車對基礎網路分流的相關問題,利用行動邊緣計算的集中式計算方式,每一輛車回報自身的資訊,包含位置、速度、行駛方向、能夠收到Hello訊息的鄰近車輛ID、能連上RSU的ID等等給行動邊緣計算伺服器。由行動邊緣計算伺服器負責收集回報的車輛資訊並試圖找到一條在進入RSU前的車對車對基礎網路的分流路徑或是在離開RSU後的車對車對基礎網路的分流路徑;本篇論文提出兩種方法分別是利用停留時間為基準的車對車對基礎網路的分流路徑選擇方法與利用分流時間為基準的車對車對基礎網路的分流路徑選擇方法。在效能評估中,在不同的車輛密度下,行動邊緣計算為基礎的分流方法優於傳統的車對基礎網路的分流方法,也就是車輛直接與RSU進行通訊的分流方式。
This thesis proposed a Mobile Edge Computing (MEC)-based n-hop away V2V2I data offloading mechanism. Let a vehicle V be communicating with its peer PX, which is in Internet, through 4G/5G cellular network and there is an IEEE 802.11p Road Side Unit (RSU) ahead of V. If there is a n-hop V2V path that can connect vehicle V with the ahead RSU before V entering into the ahead RSU’s signal coverage, the V2I offloading can be enabled, which is called VANET V2V2I offloading in this thesis. Additionally, when vehicle V has left the corresponding RSU’s signal coverage, if there is a n-hop V2V path that can connect vehicle V with the corresponding rear RSU, the V2I offloading can still be continued. This thesis proposed the Mobile Edge Computing (MEC) -based method to tackle related issues for VANET V2V2I offloading. Based on MEC’s centralized computing paradigm, each vehicle reports its context information, including location, speed, driving direction, IDs of the neighboring vehicles for which their hello message can be received, IDs of the RSUs, for which their beacons can be received, etc., to the MEC server. Thereafter, the MEC server gather reported context information to find a VANET n-hop V2V2I offloading path vehicle V before V entering into the signal coverage of the ahead RSU or after V has left the signal coverage of the rear RSU. Two methods called the Staying Time-based V2V2I offloading path Selection (STS) and the k-hop-limited Offloading Time-based V2V2I offloading path Selection (k-hop-limited OTS) were proposed in this thesis. The performance analysis shown that the proposed MEC-based offloading methods outperform the traditional V2I offloading method, i.e., have the self V2I offloading when the vehicle is inside the signal coverage of the RSU, in different vehicle density’s situations.
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