| 研究生: |
王進蒼 Wang, Jin-Chang |
|---|---|
| 論文名稱: |
基於網路流量之嵌入式系統優先權化工作排程方法 Prioritized Traffic-Dependent Task Scheduling Approach in Embedded Operation Systems |
| 指導教授: |
郭耀煌
Kuo, Yau-Hwang 郭淑美 Guo, Shu-Mei |
| 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: | 2002 |
| 畢業學年度: | 90 |
| 語文別: | 英文 |
| 論文頁數: | 78 |
| 中文關鍵詞: | 嵌入式系統優先權化工作排程 |
| 外文關鍵詞: | Prioritized Traffic-Dependent Task Scheduling |
| 相關次數: | 點閱:56 下載:4 |
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本論文提出一個基於網路流量之嵌入式系統優先權化(PRIFIC)工作排程方法。此管理方法藉由動態分配系統資源的方式,不僅能提高系統資源之使用率,同時更能有效免除因較高優先權之工作,長時間佔有系統資源所造成的網路資料遺失率上升。此管理方法乃是先萃取網路流量特徵,再藉由網路流量預測模型以及一個稱為主要成份分析(PCA)的演算法進行流量預測,最後配合一個適應性的網路工作排程模型進行資源之分配。PCA演算法主要是用來減少網路流量特徵的維度,它能夠有效率地減少網路流量預測演算法的計算複雜性。
簡而言之, PRIFIC 排程法具有網路流量預測和保證服務品質的能力。依據實驗結果可得知此管理方法在固定流率及隨機流率形態資料之網路工作排程上均有很好的表現。
This thesis proposes a PRIoritized TrafFIC-dependent (PRIFIC) task scheduling scheme based on the traffic prediction approach that. The PRIFIC manages network tasks by dynamically allocating system resources, so that it can not only prevent the network tasks from starvation state but also improve the utilization of system resources. The PRIFIC is constructed by employing an eigentraffic feature extraction model, a traffic prediction model, and an adaptive task scheduling model. Besides, an additional reference algorithm which is called principal component analysis (PCA) is adopted to reduce the dimensions of traffic features. It can efficiently reduce the computation complexity of the proposed PRIFIC algorithm.
In summary, the PRIFIC has advantages of traffic prediction and QoS-enabling. According to the simulation results, the proposed PRIFIC exhibits excellent task scheduling performance in both constant traffic and random traffic applications.
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