| 研究生: |
涂哲源 Tu, Che-Yuan |
|---|---|
| 論文名稱: |
建構在ARM平台上的效能評估器 Perfromance Evaluator Based on ARM Platform |
| 指導教授: |
鄭芳田
Cheng, Fan-Tien 洪敏雄 Hung, Min-Hsiung 楊浩青 Yang, Hao-Ching |
| 學位類別: |
碩士 Master |
| 系所名稱: |
電機資訊學院 - 製造工程研究所 Institute of Manufacturing Engineering |
| 論文出版年: | 2006 |
| 畢業學年度: | 94 |
| 語文別: | 中文 |
| 論文頁數: | 113 |
| 中文關鍵詞: | 簡易網路管理協定 、嵌入式系統 、效能指標 |
| 外文關鍵詞: | Performance Index, Embedded System, Simple Network Management Protocol (SNMP) |
| 相關次數: | 點閱:140 下載:2 |
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隨著資訊科技的進步,越來越多不同的產業開始審慎考慮導入資訊系統的效益,適時的導入符合實際需求的資訊系統的確能為企業帶來組織面、管理面及科技面正面的綜效。實用的資訊系統不論對企業或是個人都佔有舉足輕重的地位,因此資訊系統的可靠度對使用者來說相當重要,一旦資訊系統的可靠度不佳,則其為企業或是個人所帶來的損失將無可估計。近年來軟體老化的現象被提出:資訊應用系統因關鍵資源耗盡造成效能衰減及失效。
針對此現象本研究延續了原本的具預測應用伺服器失效能力之效能評估器(Performance Evaluator, PEV)的架構,採用Platform-Based Design的方法論,並以ARM平台與Embedded Linux為核心技術來開發一個基於ARM平台的效能評估器,該平台並採用簡易網路管理協定(SNMP)與一套遠端網路監控系統-Cacti為基礎開發技術。效能評估器有兩個主要的核心模組:效能偵測模組與失效預測模組。在效能偵測模組上我們提出了一個效能指標(PI)來判斷應用伺服器的效能狀態,該模組並使用系統反應時間(Response Time)與快速傅利葉轉換(FFT)來驗證模組的準確性。另外,失效預測模組則是以Lagrange Polynomial來建構的,當效能偵測模組發現應用伺服器效能發生異常時,將會通知失效預測模組根據剩餘的可用資源來預測該應用伺服器之失效時間(Time to Failure),最後效能評估器可提供失效時間等訊息給應用程式叢集服務APCS (Application Cluster Service),使其可提前轉換即將失效的服務,俾達成服務不中斷的境界。
In recent years, the issue of “Software Aging” has been proposed and studied. The exhaustion of key resources causes the performance decline and failure of an application server and even worse the entire information application system.
Aiming at this issue, this research extends the original framework of Performance Evaluator (PEV), adopts the Platform-Based Design methodology, employs ARM Platform and Embedded Linux as the central techniques to develop an ARM-based performance evaluator. The developed PEV platform incorporates both the Simple Network Management Protocol (SNMP) and a remote network monitoring system, called Cacti.
Detection Module and Prediction Module are two kernel modules of the PEV. We propose a performance index to determine the performance status of application servers. The response time and fast Fourier transform are used to verify the accuracy of the Detection Module. In addition, the Prediction Module is constructed by using Lagrange polynomial. When Detection Module detects performance anomalies of application server, it will inform Prediction Module to predict the “Time to Failure” of the application server according to the residual available resources. Lastly, PEV provides the “Time to Failure” and relative messages to the application cluster service (APCS) to perform the failover of failed services before the upcoming system breakdown to achieve near-zero downtime services.
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