網格節點工作排程分析模型設計之研究

文化大學機構典藏 CCUR > 商學院 > 資訊管理學系暨資訊管理研究所 > 博碩士論文 > Item 987654321/19969

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题名:	網格節點工作排程分析模型設計之研究
作者:	蔡志廷
贡献者:	資訊管理學系
关键词:	網格運算資源分配
日期:	2010
上传时间:	2011-10-27 14:43:09 (UTC+8)
摘要:	網格計算(grid computing)已定義出完整協同合作架構，各節點皆可分享資源與協同運算。網格環境內所有被使用之動態資源都必須被監控與分析，因此如何監控與配置網格內各節點動態資源以執行工作一直是重要的議題。　　本研究提出兩種網格節點工作排程分析模型，一為非群組化模型，另一為群組化模型。非群組化網格節點工作排程分析模型，係使用者於某一節點交付工作時，該節點依收集之資訊與工作分配演算法將工作配置於適當節點執行；意即，非群組化網格節點工作排程分析模型可即時監控網格各節點之動態資訊及配置資源，進而提升網格整體效能；由於，CPU行節點資源監控造成之消耗使非群組化模型適用在五十個節點以下之網格環境。群組化網格節點工作排程分析模型，係諸節點先以CPU規格進行分類，在各分類下以每群組節點數不超過十個進行分群，可有效減少節點因CPU行資源監控造成之消耗。群組代理節點負責群組間資源之配置，可有效提升群組間之資源使用率。此群組化模型，適用於五十個以上之節點數。透過實作上述兩種節點工作排程分析模型，可知此二模型可有效提升整體網格效能。 A collaborated framework of grid computing was well defined, every grid node would be able to share resources and collaborate with each other. In grid environment, every dynamically used resources should be monitored and analyzed. How should we monitor and allocate dynamic resources in grid is an important issue all the time. In this thesis, there are two different types of process scheduling model, one is non-grouped grid node process scheduling model and the other one is grouped grid node process scheduling model. With non-grouped grid node process scheduling model, users could assign jobs at any node in the grid, and this node would dispatch those jobs based on collected information of resources and job scheduling algorithm. That is to say the overall performance of grid environment would be improved because non-grouped grid node process scheduling model could monitor and allocate dynamic resources. However, there is a CPU consumption caused by monitoring dynamic resources in grid. The non-grouped grid node process scheduling model is not suitable when there are more than fifty nodes in the grid environment. With grouped grid node process scheduling model, nodes would be classified into five classifications by the CPU specification scores. Within each classification, every node in the same classification would be assigned to a group which is no more than ten nodes in that group. By separating nodes into groups, the CPU consumption caused by monitoring the resources of nodes in a group would be effectively reduced. While the group-agents node deal with all the resource allocation between groups, the utility ratio of the grid resource would be increase. Grouped process scheduling grid node model could be implemented in the grid with more than fifty nodes. By implementing these two types of process scheduling model, the overall performance of grid would be improved.
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