博碩士論文 103522060 詳細資訊




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姓名 蔡明勳(Ming-Shiun Tsai)  查詢紙本館藏   畢業系所 資訊工程學系
論文名稱 在整合虛擬化雲端平台上進行快速自動擴展之研究
(Study of Rapid Auto-Scaling for Integrated Virtualization Cloud Platforms)
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摘要(中) 隨著網路科技的發展,為了降低網路服務的營運成本、增加服務延展性,雲端技術是目前最流行的解決方案。為了增加服務部署的彈性,各國的虛擬化服務生紛紛投入Container虛擬化技術。有別於Hypervisor技術,Container提供更輕量化、更加彈性的部署,但是共用作業系統的特性也為Container技術帶來資訊安全上面的隱憂。本論文參考歐洲通訊標準協會 (European Telecommunications Standards Institute, ETSI)所提出的網路功能虛擬化 (Network Function Virtualization, NFV)架構及Rancher 專案整合Hypervisor及Container兩種虛擬化技術,建置一個混和虛擬化雲端平台 (Integrated Virtualization Cloud, IV Cloud)平台,提供網路服務商部署虛擬網路功能 (Virtual Network Function, VNF)。本論文提出基於模糊理論的即時自動擴展機制 (Fuzzy-based Real-time mechanism for Auto-Scaling, FARS),此機制可以提供網路服務商一個動態、快速及低成本的自動擴展的資源配置解決方案。此外本論文亦設計個安全部署機制於IV Cloud平台提供服務商針對不同層級的安全需求對VNF進行安全部署。
摘要(英) With the rapid development of internet technology, to reduce internet service operating expenses and increase scaling of service, cloud computing is one of a most popular solution. To increase the elasticity of service deployment and reduce cost, cloud service operator has invested a lot of research resource to container virtualization technology. Unlike hypervisor, the container provides lightweight and elastic deployment. Service security issues may appear in the container with a shared kernel. In this thesis, according to the Network Functions Virtualization (NFV) Architecture Framework proposed by European Telecommunications Standards Institute (ETSI) and Rancher project build an Integrated Virtualization Cloud (IV Cloud) with hypervisor and container technology. IV Cloud provides the Virtual Network Function (VNF) deployment。This thesis proposed a Fuzzy-based Real-time mechanism for Auto-Scaling(FARS). FARS provides a dynamic, rapid and lower-cost auto-scaling method. Moreover, we provide and implement a security deployment mechanism in IV Cloud. This mechanism provides service operator different security level of VNF deployment.
關鍵字(中) ★ 自動擴展
★ 安全部署
★ 虛擬網路功能
★ 雲端平台
關鍵字(英)
論文目次 第一章 緒論 1
1.1 概要 1
1.2 研究動機 2
1.3 研究目的 3
1.4 章節架構 3
第二章 背景知識與相關研究 4
2.1 Hypervisor與Container虛擬化技術 4
(1) Hypervisor 虛擬化技術 5
(2) Container 虛擬化技術 6
(3) Container與Hypervisor比較 6
(4) Integrated Virtualization Clouds與安全部署 7
(5) 雲端服務的計費方式 9
2.2 Docker 10
2.3 Auto-Scaling 12
(1) 排程式自動擴展 (Scheduled Auto-Scaling): 13
(2) 預測式自動擴展 (Predictive Auto-Scaling): 14
(3) 反應式自動擴展(Reactive Auto-Scaling): 14
(1) 垂直擴展 15
(2) 水平擴展 15
2.4 模糊理論 16
(1) 模糊化 (Fuzzification) 17
(2) 模糊資料庫及模糊推論引擎 18
(3) 解模糊化 20
2.5 相關研究比較 21
第三章 研究方法 25
3.1 系統平台 25
(1) IV Cloud平台部署架構 25
3.2 系統運作流程與機制 27
(1) 基礎設施 28
(2) Hypervisor 28
(3) Docker Agent 29
(4) Network Agent 29
(5) Orchestrator 31
(6) 效能資料收集 32
(7) 負載平衡、高可用性及VNF健康檢查 34
(8) 自動擴展機制 35
(9) 自動擴展機制假設與限制 36
(10) FRAS演算法 37
第四章 實驗與討論 44
4.1 實驗平台 44
4.2 IV Cloud平台基本網路功能測試 47
(1) 實驗一 整合虛擬化平台效能測試 47
(2) 實驗二 Container Loopback Network測試 49
(3) 實驗三 跨越Docker Daemon網路頻寬測試 50
(4) 實驗四 Docker跨越Hypervisor的頻寬測試 52
(5) 實驗五 Docker跨越實體網路的頻寬測試 53
(6) 實驗六 Virtual NFVI的效能監測 55
(7) 實驗七 實體網路的效能監測 56
(8) 實驗八 大量部署測試 57
(9) 實驗九 Dockerlize Linux的大量部署測試 60
4.3 Auto-Scaling測試比較 61
(1) 實驗十 Load Balancer功能性測試 61
(2) 實驗十一 Auto-Scaling演算法比較 62
4.4 VNF的安全部署 79
實驗十二 安全部署測試 79
4.5 實驗結論 80
第五章 結論與未來研究 82
5.1 結論 82
5.2 未來研究 83
參考文獻 85
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指導教授 周立德(Li-Der Chou) 審核日期 2016-8-30
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