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研究生： 呂享倫
Hsiang-Lun Lu
論文名稱： 基於網路負載之虛擬叢集負載平衡佈署策略
Efficient Resource Provisioning for Virtual Cluster Deployment Based on Network WorkloadNetwork Workload
指導教授： 王尉任
Wei-Jen Wang
口試委員:
學位類別： 碩士
Master
系所名稱： 資訊電機學院 - 資訊工程學系
Department of Computer Science & Information Engineering
論文出版年： 2014
畢業學年度： 102
語文別： 中文
論文頁數： 54
中文關鍵詞： 雲端計算 、OpenStack 、Virtual Cluster 、VM Placement 、Virtual Cluster Placement
外文關鍵詞： Cloud computing, OpenStack, Virtual Cluster, VM Placement, Virtual Cluster Placement
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    • 基礎架構服務(Infrastructure-as-a-Service)是雲端服務的重要類型之一，它使用逐漸成熟的虛擬化技術(Virtualization Technology)，將傳統的硬體資源以軟體的方式虛擬化呈現與整合多個虛擬機器(Virtual Machine) ，來運行服務或提供使用者使用，以此提高實體機器(Physical Machine)資源的使用效率與彈性。除了虛擬機器的虛擬化技術外，網路虛擬化是近年來用來強化IaaS的技術，可提供使用者設定自己所需的網路環境，並且建立自己所需的虛擬叢集(Virtual Cluster)或是虛擬機房(Virtual Datacenter)。然而，利用人工進行虛擬機房的建置與管理會造成效率的問題，也不適合管理大量動態產生與關閉的虛擬機房。因此我們研發虛擬機房的管理軟體SAMEVEDStackV2，來解決虛擬叢集與虛擬機房的資源配置與管理問題。SAMEVEDStackV2是由開放原始碼專案OpenStack所延伸發展的系統，它利用我們發展的虛擬機房監控機制來擷取虛擬叢集的資源使用量，做為系統資源配置的參考。此外，我們利用虛擬機房上的應用程式的特性去設計新的排程演算法，使得虛擬叢集配置時可以考慮實體機器負載，讓實體網路的負載達到最小化可能。我們透過多種實驗案例的測試與調整，發現我們的佈署策略在多組虛擬叢集的運算情況下可讓實體網路的負載大幅降低，但對於CPU使用量卻只有少量的影響。

    Infrastructure-as-a-Service (IaaS) is an important type of cloud service. It uses server virtualization technology to provide users the software-based virtual machines as the computing power over the physical computing resources in a datacenter, such that the physical computing resources can achieve better utilization rate and manageability. The network virtualization technology is another key technology of IaaS, which can create virtual network environments on top of the physical network environment. With server virtualization and network virtualization, the IaaS users are able to create user-defined virtual clusters/datacenter. The problem is that, manual resources allocation and management for virtual clusters/datacenters is not practical because setting up virtual clusters/datacenters is time-consuming. In addition, the virtual cluster/datacenter placement problem is challenging because we need to consider the constraints of physical resources as well as the relationship among the virtual resources. To solve these problems, we have developed an IaaS management system, SAMEVEDStackV2, based on an open-source software package, OpenStack. The SAMEVEDStackV2 supports a high-level API for virtual clusters/datacenters management, and uses a monitoring/profiling mechanism for tracking and classifying virtual clusters/datacenters. The scheduler uses the information of virtual clusters/datacenters to reduce unnecessary network bandwidth consumption while placing virtual cluster/datacenters on physical computing resources. Our preliminary experimental results show that, the proposed placement strategy can reduce 37% of the physical network bandwidth consumption when comparing with the default OpenStack scheduler.

    摘要 i Abstract ii 目錄 iii 圖目錄 v 表目錄 vi 第一章 緒論 1 1-1 前言 1 1-2 問題與實作目標 3 1-3 論文貢獻 5 1-4 論文架構 6 第二章 相關研究 7 2-1 背景知識 7 2-1-1 虛擬叢集與虛擬機房 7 2-1-2 網路虛擬化技術 9 2-2 相關系統 11 2-2-1 OpenStack 11 2-2-2 SAMEVED與CSEP 12 2-2-3 SAMEVEDStackV1 13 2-3 相關排程策略 14 2-3-1 OpenStack Filter Scheduler 14 2-3-2 Detecting and Managing VM Ensembles in Virtualized Data Centers 15 2-3-3 HPC-Aware VM Placement in Infrastructure Clouds 17 2-3-4 Virtual Machine Provisioning Based on Analytical Performance and QoS in Cloud Computing Environments 17 第三章 系統設計 18 3-1 系統架構 18 3-1-1 SAMEVEDStackV2 Compute Controller 19 3-1-2 SAMEVEDStackV2 API Interface 21 3-1-3 SAMEVEDStackV2 Profiling Monitor 21 3-1-4 SAMEVEDStackV2 Neutron 23 3-1-5 其他元件 24 3-2 系統排程與監控 25 3-2-1 系統資源監控 25 3-2-2 虛擬叢集分類 25 3-2-3 系統排程策略 26 第四章 實驗環境與量測 28 4-1 實驗背景與情境假設 28 4-2 實驗案例 29 4-3 實驗結果與討論 32 4-3-1 實驗一：虛擬叢集分類 32 4-3-2 實驗二：整體使用率 33 第五章 結論 36 第六章 未來研究方向 37 6-1 叢集內部溝通監控與配置 37 6-2 叢集成員動態遷移 37 6-3 排程優化 37 參考資料 39 附錄一 SAMEVEDStack比較表 42 附錄二 實體機器硬體規格 44 附錄三 作業系統需求與軟體版本 45

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