Green Cloud Computing 班 級 : 資 管 碩 一 組 員 : 黃 宗 緯 朱 雅 甜

Transcription

1 Green Cloud Computing 班 級 : 資 管 碩 一 組 員 : 黃 宗 緯 朱 雅 甜

2 Outline Introduction Proposed Schemes VM configuration VM Live Migration Comparison 2

3 Introduction (1/2) In 2006, the power consumption of computing data center was about 61 billion kwh(kilowatt hour). In 2011, the power consumption of computing data center was over 100 billion kwh. Since data centers operate at only 20-30% utilization, 70-80% of this consumption is lost due to over-provisioned idle resources. 3

4 Introduction (2/2) Server Server Server Virtualization software Server VM 1 quantification of computing resource VM 2 quantification of computing resource VM 3 quantification of computing resource VM 4 quantification of computing resource Distribution VM 1 Personal application Internet VM 2 VM 3 Network applications Virtual machine in a cloud infrastructure VM 4 VM 5 VM Mainframe applications 4

5 Paper 1 Model-driven Auto-scaling of Green Cloud Computing Infrastructure Source:Future Generation Computer Systems, Vol. 28, pp , 2012 Authors:Brian Dougherty, Jules White and Douglas C. Schmidt SCORCH (Smart Cloud Optimization for Resource Configuration Handling) 5

6 Auto-Scaling Auto-scaling is an important cloud computing technique that dynamically allocates computational resources to applications to match their current loads precisely. No Yes Auto-scaling in a cloud infrastructure 6

7 Challenge Computing VM configuration options and constraints. Selecting VM configurations to ensure auto-scaling speed requirements. Optimizing the queue size and configuration to minimize the energy consumption and operating costs. 7

8 Feature VM Application Application Server Server OS OS Feature, f1 Ubuntu 9.10 Processor Processor Feature, f2 Feature, f3 Feature, f13 Feature, f14 Feature, f15 Feature, f16 Windows 7 Redhat 9 Small Medium Large ExtraLarge Feature, f4 JBOSS Feature, f7 Feature, f10 Tomcat JBOSS v6 JBOSS v5 Tomcat v6 Tomcat v5.5 Feature, f5 Feature, f6 Feature, f8 Feature, f9 Feature model Jetty Jetty v7 Jetty v6.1 Feature, f11 Feature, f12 8

9 SCORCH Demand Features Time Power Cost Options Optimal SCORCH model-driven process 9

10 Paper 2 Green Cloud: A New Architecture for Green Data Center Source:In Proceedings of the ACM ICAC-INDST 2009 conference on Autonomic computing and communications industry session, pp , 2009 Authors:Liang Liu, Hao Wang, Xue Liu, Xing Jin, WenBo He, QingBo Wang and Ying Chen 10

11 Live Migration Optimize the utilization of available resources (e.g., CPU) A VM is moved from on physical server to another while continuously running. Providing an illusion of seamless migration

12 Performance Metric static and dynamic power dissipation a server with zero workload consumes about 60% of its peak power The acceptable quality for an online game requires round trip time (RTT) less than ms.

13 Green Cloud Architecture

14 Heuristic algorithm

15 Paper 3 Adaptive Threshold-Based Approach for Energy-Efficient Consolidation of Virtual Machines in Cloud Data Centers Source:In Proceedings of the ACM MGC 2010 conference on Middleware for Grids, Clouds and e-science, 2010 Authors:Anton Beloglazov and Rajkumar Buyya 15

16 SLA U j U a j r t t :requested MIPS by all the VMs :actually allocated MIPS M :number of VMs SLA Violation Metric M j 1 t U M j 1 r j t t U U r j t t This metric represents the percentage CPU performance that has not been allocated when demanded by applications relatively to the total demand a j dt dt

17 Allocation Policies (1/2) the CPU utilization of a host falls below the lower threshold, the utilization exceeds the upper threshold

18 Allocation Policies (2/2) Minimization of Migrations (MM) Highest Potential Growth (HPG) Random Choice (RC)

19 Upper Utilization Threshold 19

20 Lower Utilization threshold U i 30% 20

21 Dynamic Thresholds

22 Modified Best Fit Decreasing

23 Method Comparison SCORCH Single Threshold Adaptive Threshold Object Amazon EC2 IBM X336 Amazon EC2 Non-Method Power Consumption (kw) Method Power Consumption (kw) Power Consumption Percentage Reduction 120, ,204 60, % 53% 28% Percentage Reduction SCORCH Single Threshold Adaptive Threshold Method 23

24 Q & A Question: Assume that each host have 4 VMs(A, B, C, D) and the highest CPU performance of each host is 98%, if the 4 VMs want to require the CPU resource from the host in the same time. Based on the SLA, which option could remove the VMs 1. host1 A: 25%, B: 15%, C:30%, D:10% 2. host2 A: 20%, B: 20%, C:20%, D:20% 3. host3 A: 20%, B: 25%, C:10%, D:35% 4. host4 A: 25%, B: 25%, C:25%, D:25% Answer: 4 24

25 The End 25