| 研究生: |
徐凰碩 Hsu, Huang-shuo |
|---|---|
| 論文名稱: |
WiMedia-based無線個人網路之路由協定效能評估 Performance Evaluation of routing protocols for WiMedia-based WPANs |
| 指導教授: |
郭文光
Kuo, Wen-Kuang |
| 學位類別: |
碩士 Master |
| 系所名稱: |
電機資訊學院 - 電腦與通信工程研究所 Institute of Computer & Communication Engineering |
| 論文出版年: | 2008 |
| 畢業學年度: | 96 |
| 語文別: | 中文 |
| 論文頁數: | 53 |
| 中文關鍵詞: | 效能評估 、模擬 、無線個人網路 |
| 外文關鍵詞: | AODV, MBOA, simulation, WPANs, DSR, Wimedia |
| 相關次數: | 點閱:209 下載:0 |
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WiMedia-Based 無線個人網路簡稱 MBOA,是一種分散式的媒介存取機制,和以往需要中央控制中心分配頻寬的方式不同,而是每個裝置在傳輸範圍內都可以藉由發信標去競爭通道以協調傳送的時間。由於 MBOA 是採取分散式的方式架構,比目前大家所熟知的IEEE 802.11更適合用於移動以及個人行動網路上面,而不用受制於某個中央管理裝置(EX. Access Point),傳送都必須透過此中央管理裝置去傳送和分配頻寬,真正達到點對點直接傳送的方式傳送資料。
在大家所熟知的Routing上面可以分為三大類,分別為Table-Driven、 On-Demand、Hybrid。不過在移動的狀況下,Table-Driven因為路徑要適應快速的移動所需付出的控制封包量太大,對於傳送資料的效率不高。所以這篇論文使用AODV和DSR這兩種最常見的On-Demand Routing去針對移動的狀態,整合上述所說的MBOA媒介存取層,建立一個模擬的平台並對於高速資料傳輸的效能去作一個評估,以期待之後能利用這個平台去做更多有關跨層最佳化相關的研究和實驗。
WiMedia-based wireless personal network (MBOA) is a distributed media access control mechanism. Different from centralized MAC mechanism which allocates bandwidth by central device in previous technique, each device of MBOA can compete for the channel in order to be allocated time to transmit data by sending beacons in transmitting range. Because of its distributed structure, MBOA is more suitable than IEEE 802.11 adapting to mobile devices and personal mobile network. It doesn’t need any central device (EX. Access Point) to manage the devices for data transmitting, and can realize transmitting packets directly in the point-to-point way.
It is well known that routing can be divided into three classes: Table-Driven, On-Demand and Hybrid. But under the situation of moving, it costs too many control packages to maintain routing information. The efficiency of transmitting data packet is very low.
This thesis is using AODV and DSR which are the two most common On-Demand Routing protocols for mobile model over MBOA. We also set up one platform of simulation and give evaluation of efficiency on high-speed data transmission and we look forward to utilizing the platform to do more research and experiments correlated with cross-layer optimization.
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