雲端開發平台之建置經常需要花費大量的時間安裝與設定環境，不難想像，當雲端服務系統需要更新或者遷移時所需付出的成本將隨著系統擴增而急速上升。因此，我們希望藉由將預先安裝好的R語言程式開發平台包裝成Turnkey的型式，用戶只需要簡易安裝Turnkey的執行環境－Docker，並將Turnkey掛載於其上，便能快速建置與部署雲端服務平台，如此不論用戶想要更新或者遷移整個雲端平台，只需要將更新後的Turnkey重新掛載或者遷移至新的雲端環境，不再需要重新安裝與設定所有機器，有效的減少雲端開發平台重新建置時所必須付出的龐大成本。
在雲端服務平台之中，運算資源也是不可或缺的存在，為了避免過剩的運算節點造成資源浪費，我們針對運算資源管理設計了一套動態調節(Dynamic Provisioning)機制，藉由在每個執行的運算單元中加入timeout機制，適時增加與刪減運算節點之數量，藉此減少資源浪費與不足的情形發生，達到有效使用雲端資源的目的。
除此之外，為了使開發平台服務更具可攜性(Portability)，不論是整合式開發環境-Rstudio，或者是應用程式之上傳與部署介面，我們皆採取網頁形式呈現，用戶只需透過瀏覽器即可在個人電腦、行動裝置等多種前端平台上開發個人的策略腳本，不再受限於硬體設備與作業系統，有效的提高整體系統的可攜性。

Cloud development platform development with traditional virtual machine has always been too complex, too expensive, and too slow, therefore we hope to reduce costs by replacing traditional virtual machine with docker container. We build the cloud development platform which can run R language program on the docker container and make it to a turnkey. The user can update, migrate and run the turnkey quickly without reinstalling or resetting the host. It will reduce the cost of re-building the cloud development platform effectively.
In the cloud service platform, the computing resources are very precious. We design a dynamic provisioning mechanism for them so as to avoid redundant compute nodes. We adjust the number of compute nodes by timeout mechanism. When the running job is timeout, it means the system is too busy, and then we need to provide more compute nodes. When the utilization of compute nodes are too low, we will remove some compute nodes to reduce waste of resources.
In order to make our platform services have more portability, we implement our platform service on the web server. The users can using the platform service including the IDE (Rstudio) and the function of deployment on the PC, netbook or any mobile device (e.g. smart phone, tablet PC). The user will not be limited by hardware device and it will incresase the portability of system effectively.

論文審定書 i
致謝 ii
摘要 iii
Abstract iii
目錄… iv
圖目錄 vii
表目錄 ix
第 一 章 序論 1
1.1 研究動機與目的 1
1.2 研究步驟 2
1.3 章節介紹 3
第 二 章 研究背景 4
2.1 雲端運算及雲端開發平台介紹 4
2.1.1 雲端運算 4
2.1.2 雲端開發平台 4
2.2 Linux Container介紹 5
2.2.1 Linux Container架構 5
2.2.2 Container與Virtual Machine比較 6
2.3 Docker介紹 8
2.3.1 Docker container四大特性 9
2.3.1.1 隔離性 10
2.3.1.2 可配額/可度量 11
2.3.1.3 移動性 11
2.3.1.4 安全性 12
2.4 R及Rstudio介紹 13
2.4.1 R 13
2.4.2 RStudio 13
2.5 加密機制 14
2.5.1 AES 15
2.5.2 RSA 18
第 三 章 系統設計 21
3.1 系統介紹 21
3.1.1 系統環境的建置 21
3.1.2 系統功能 21
3.1.3 系統限制 22
3.1.4 名詞解釋 22
3.2 系統架構設計 23
3.2.1 系統架構 23
3.2.2 系統運作流程 25
第 四 章 系統實作 26
4.1 Deployment node 26
4.1.1 程式開發 27
4.1.2 部署程式 28
4.1.3 執行策略 29
4.2 Compute node 29
4.2.1 Compute-Node-Disposition-Control-Algorithm 31
4.3 Security 32
4.4 工作排程機制 33
4.5 工作排程與運算節點動態調整機制流程 35
4.6 自動檢查並安裝R套件 37
4.7 節點關聯 38
4.7.1 運算節點註冊 38
4.7.1.1 節點註冊API 38
4.7.1.2 註冊Physical Machine 39
4.7.1.3 註冊Container 39
4.7.2 開發節點與部署節點登入帳號傳遞 40
4.7.3 部署節點與運算節點即時訊號傳遞 41
4.7.4 部署節點與運算節點檔案分享 41
4.7.5 工作派送與停止 42
4.8 使用者介面 44
4.8.1 登入與註冊介面 44
4.8.1.1 登入介面 44
4.8.1.2 註冊介面 45
4.8.2 策略部署與管理介面 46
4.8.3 策略開發介面 48
4.8.4 結果顯示與歷史訊息介面 49
4.8.4.1 結果顯示 49
4.8.4.2 歷史資訊介面 49
第 五 章 效能分析與調校 50
5.1 實驗環境 50
5.2 實驗設計 50
5.3 前置實驗與實驗結果 53
5.3.1 前置實驗 53
5.3.2 實驗一 54
5.3.3 實驗二 55
5.3.4 實驗三 56
第 六 章 結論與未來展望 58
參考文獻 60
附錄1 63
I. Introduction 63
II. Related Work 63
III. System Overview 64
IV. System Implementation 65
V. Simulated Result 68
VI. Conclusion 70
VII. References 71
附錄2 72

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