雲端儲存隨著頻寬的提升而蓬勃發展，越來越多的資源被投入到雲端儲存。在論文中我們設計一套雲端儲存系統，由單一主伺服器和多個資料伺服器組成。主伺服器控制整個系統，例如管理資料伺服器，並且週期性的取得資料伺服器狀態。資料伺服器則透過Windows檔案系統將資料儲存於本地硬碟。為了因應大量的資料存取，在伺服器選擇上就必須能提供效能上的平等。在這篇論文中我們提出伺服器選擇策略，結合多個參數來做效能衡量。藉此平衡伺服器端的多個資源項目。
我們將此策略實現於我們自行設計的雲端儲存系統上，並且進行了兩個實驗，分別是上傳實驗和上傳加下載實驗。在上傳實驗中我們的演算法將可用空間的最大最小差距維持在5GB內，而隨機存取則會造成可用空間的最大最小差隨著時間發散，最高接近30GB。而上傳加下載實驗，使用我們演算法的結果，可用空間的最大最小差維持在10GB內。而隨機存取的最大最小差也是隨著時間發散，最高也接近30GB。另外在兩個實驗中，我們的演算法也有效的提升了使用者傳輸速度，上傳實驗中使用演算法的平均下載速度較隨機方式快上1.1倍。上傳加下載實驗中使用演算法的平均下載速度提升了1.03倍，平均上傳速度提升了1.1倍。

The fast growing bandwidth has made the development of cloud storage. More and more resource has put in cloud storage. In this thesis, we proposed a new cloud storage that consists of a single main server and multiple data servers. The main server controls system-wide activities such as data server management. It also periodically communicates with each data server and collects its state. Data servers store data on local disks as Windows files. In order to response to the large number of data access, Selection of the server which is necessary to offer equalized performance. In this paper, we propose a server selection algorithm using different parameters to get the performance metrics which enables us to balance multi-resource from server-side.
We design new cloud storage and implement the algorithm. According to upload experiment, the difference between the maximum and the minimum free space when using our algorithm is less than 5GB. But using the random mode, the free space difference is increased as time, and the maximum is 30GB. In the mixed experiment, we added the download mode, and our algorithm is fewer than 10GB. The result of the random mode approximated to the first experiment. Finally, our algorithm obtains 10% and 3% speedup in upload throughput by upload experiment and mixed experiment, 10% speedup in download throughput by mixed experiment.

第一章 簡介 1
1.1 研究動機 1
1.2 研究目的 2
1.3 論文大綱 2
第二章 背景知識與相關研究 3
2.1分散式檔案系統 3
2.2 多執行緒程式設計 6
2.2.1 共用變數存取同步機制 6
2.2.2臨界區段同步機制 8
2.2.3 多重讀取單一寫入同步機制 11
2.2.4 互斥器同步機制 12
2.2.5 信號同步機制 13
2.2.6 事件同步機制 13
2.3 伺服器選擇策略 15
第三章 MPD Cloud Storage與伺服器選擇策略 18
3.1 MPD Cloud Storage系統架構 18
3.2 MPD Cloud Storage軟體架構 20
3.2.1資料儲存層(Data Storage Layer) 21
3.2.2資料管理層(Data Manager Layer) 27
3.2.3應用程式介面層(Application Interface Layer)32
3.2.4雲端應用程式層(Cloud Application Layer) 34
3.3 Ratio Balance Algorithm 34
3.3.1 動機和目的 34
3.3.2 Performance Metric 36
3.3.3 Ratio Balance Algorithm用於上傳檔案 37
3.3.4 Ratio Balance Algorithm用於下載檔案 39
3.4 傳輸範例 39
3.4.1 客戶端上傳檔案 39
3.4.2客戶端下載檔案 41
3.5 Base Library 46
第四章 實作和實驗結果 54
4.1 實驗環境 54
4.2 數據與討論 56
4.2.1 實驗一，上傳模式 57
4.2.2 實驗二，上傳模式加下載模式 58
第五章 結論 62
參考文獻 63

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