研究生: |
莊秉鑫 BING-SIN JHUANG |
---|---|
論文名稱: |
針對FreeBSD作業系統之固態硬碟幾何特性分析演算法 Geometries Analyzing Algorithms of Solid-State Drives in FreeBSD |
指導教授: |
吳晋賢
Chin-Hsien Wu |
口試委員: |
林淵翔
Yuan-Hsiang Lin 陳雅淑 Ya-Shu Chen 謝仁偉 Jen-Wei Hsieh |
學位類別: |
碩士 Master |
系所名稱: |
電資學院 - 電子工程系 Department of Electronic and Computer Engineering |
論文出版年: | 2019 |
畢業學年度: | 107 |
語文別: | 中文 |
論文頁數: | 57 |
中文關鍵詞: | 固態硬碟 、偵測演算法 |
外文關鍵詞: | Solid-state drive, Detection Algorithms |
相關次數: | 點閱:165 下載:0 |
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現今固態硬碟(Solid-State Disk, SSD)因體積小、耗能低、抗震動性質高、安靜、高速存取、非揮發性記憶體等優點現已成為市面上手機、桌上型個人電腦、攜帶型個人電腦乃至各種嵌入式系統之儲存裝置的首選,此外製程技術的進步讓SSD在儲存容量以及價格上已經大幅度趕上HDD,因此越來越多雲端資料中心(Data Center)、網路附接儲存(Network Attached Storage, NAS)設備及應用以及高效能運算系統(High-Performance Computing)上的儲存裝置為了符合高速網路效能、快速儲存等特性開始選擇SSD為首選。而如何將異種SSD組成的的系統作排程優化進一步成了重要的課題之一,而為了能夠有效的優化排程勢必要先了解各個SSD本身的幾何特性來做調整,本論文為了讓異種SSD組成的資料中心能夠善用各個SSD的優點來優化整體資料中心的效能,開發了能夠在作業系統FreeBSD之下分析不同SSD之幾何特性的方法,SSD幾何特性不僅能夠當作資料中心優化的依據也可以讓一般使用者能夠有更多的選擇參考。
Nowadays, Solid-state disk (SSD) has become the best choice of storage in smart phones, Desktop Computers, Notebooks, and various embedded systems because of its brilliant advantages compared with Hard Disk Drive (HDD) such as small size, low-power consumption, high resistance of physical shock, silence, quicker access time, lower latency and non-volatile feature. Furthermore, cost per capacity of SSD are highly reduced by advanced manufacturing process technology. Therefore, more and more storage requirements of data center, applications of Network Attached Storage(NAS) and high-performing computing(HPC) systems begin to choose SSD as their best storage to achieve high-speed network performance and high I/O performance.
For the applications as mentioned above, algorithm to optimize I/O schedule in system with various SSD becomes an important issue. Before we scheduling the I/O, we must know Geometries of each SSD in system. In this thesis, we propose a Geometries Analyzing Algorithms of Solid-State Drives in FreeBSD to analyze the geometries of different SSD in FreeBSD. Afterward, we can use these geometries to optimize the I/O scheduler in data center, NAS applications and HPC systems. Also, we can provide consumers an information for choosing SSD in market.
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