臺灣博碩士論文加值系統

在這個資訊爆炸的年代，人們習慣透過網路分享各種訊息，而隨著所欲分享與儲存的資料量快速成長，資料維護的成本也隨之大幅增加。由於雲端儲存系統具備大量的儲存空間和傳輸頻寬，以及提供資料維護的服務，因此大幅降低了資料管理上的成本，所以，許多公司開始選擇將資料外包給雲端儲存系統做管理與維護。然而，因為使用者不再實際掌控資料，資料的安全性與可得性一直是雲端儲存系統上被關注的焦點，而如何在資料安全性、資料可得性、存取效能以及使用者成本上達成平衡則是本論文所要探討的議題。
由於現今雲端儲存系統的提供者僅提供使用者制式化的服務層級協定，使用者無法得到真正符合使用者需求的服務。因此本論文首先依據使用者的四大需求重新定義了相關的服務層級協定條款。根據使用者簽訂的客製化服務層級協定，
我們可以得知使用者真正的需求，並調整系統以完成服務。
在現有支援資料安全的雲端儲存系統中，基於簡短秘密分享的雲端儲存系統具備最小所需儲存空間、高執行效能以及支援金鑰管理機制的優點。藉由調整簡短秘密分享的參數(n, k)，系統將能提供不同程度的安全性、可得性保護，但也面臨著不同程度的存取效能及客戶端成本。本篇論文將基於此類雲端儲存系統進一步探討如何在滿足使用者所簽訂的客製化服務層級協定下調整此系統之參數(n, k)以達到最佳化的儲存效果。
最後，透過分析數個虛擬情境，我們模擬不同使用者根據自身需求簽署不同的服務層級協定。最後，模擬了使用者在不同雲端服務提供者的環境中，系統所取得的最佳化結果。

In the era of information explosion, people usually share various kinds of information through networks. As more information is going to be shared and stored, the maintenance costs of data also increase. Since cloud storage systems have large storage space, high transmission bandwidth, and the supports of data maintenance, the management costs of clients can further be reduced, and therefore more companies would like to outsource their data into cloud storage systems. However, because of the lacks of physical controls of data, the data security and the data availability are always concerned. Hence, this thesis mainly focuses on proposing a method to leverage between the data security, the data availability, the access performance, and the client cost.
Nevertheless, clients often cannot be served with what they actually want because the Service Level Agreement (SLA) provided by existing cloud storage systems is not customized. Therefore, this thesis first defines the corresponding SLA elements according to the four major concerns of clients. Based on the customized SLA negotiated with clients, their actual requirements can be discovered and exploited to adjust the system parameters for completing services.
Among existing cloud storage systems with the data security support, Short-Secret-Sharing (SSS) cloud storage system has the characteristics including the smallest storage consumption, the highest performance and key management supports. By adjusting the parameters (n, k) of SSS, the cloud storage system can provide different levels of protection in the data security and the data availability whereas obtaining different access performance and client costs. This thesis would like to propose a method to obtain the optimal result by adjusting the parameters (n, k) based on the customized SLA of clients.
Finally, by analyzing several scenarios, the customized SLAs negotiated with different clients are obtained. Moreover, optimal results are presented when clients are served by different cloud storage systems.

List of Table VIII
List of Figures IX
Chapter 1. Introduction 1
1.1 Background 1
1.2 Motivation 2
1.3 Contribution 2
1.4 Organization of the Thesis 3
Chapter 2. Related Work 4
2.1 Existing Cloud Storage Systems 4
2.1.1 Replication with share keys 5
2.1.2 Threshold secret sharing with local encryption 5
2.1.3 Short Secret Sharing 6
2.2 Short-Secret-Sharing Cloud Storage 6
2.2.1 Secret Sharing 7
2.2.2 Short Secret Sharing 8
2.2.3 Short Secret Sharing in Cloud Storage System 9
Chapter 3. SLA-aware Short-Secret-Sharing Cloud Storage System 12
3.1 System Architecture and Component Description 12
3.1.1 System Management 13
3.1.2 Security Component 14
3.1.3 Resource Management Component 15
3.2 System Operations 16
3.2.1 Data Upload 16
3.2.2 Data Download 17
3.3 Definition of SLA Element 18
3.3.1 Data security 18
3.3.2 Data Availability 19
3.3.3 Access Performance 19
3.3.4 Client Cost 20
3.4 SLA Element Modeling 21
3.4.1 Data Security Modeling 22
3.4.2 Data Availability Modeling 26
3.4.3 Access Performance Modeling 28
3.4.4 Client Cost Modeling 32
Chapter 4. Scenario Descriptions and Problem Formulation 34
4.1 SLA in SLA-aware SSS Cloud Storage 34
4.2 Scenario 1 35
4.2.1 System Environment 35
4.2.2 Client Requirements and SLA Elements 35
4.2.3 Problem Formulation for Scenario 1 36
4.2.4 The Optimal Solution of Scenario 1 37
4.3 Scenario 2 38
4.3.1 System Environment 38
4.3.2 Client Requirements and SLA Elements 39
4.3.3 Problem Formulation for Scenario 2 39
4.3.4 The Optimal Solution of Scenario 2 40
Chapter 5. Conclusions and Future Work 41
References 42

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