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Resource Management in Virtualization-based Data Centers
Resource Management in Virtualization-based Data Centers
Data Center
Data Center
Resource Management in Data Centers
Resource Management in Data Centers
Resource Management in Data Centers
Resource Management in Data Centers
Motivation for Virtualized Hosting in Data Centers
Motivation for Virtualized Hosting in Data Centers
The Xen Virtual Machine Monitor
The Xen Virtual Machine Monitor
Outline
Outline
Xen-based Data Center
Xen-based Data Center
Resource Usage Accounting
Resource Usage Accounting
Resource Allocation
Resource Allocation
Intelligent Scheduling of Distributed Applications
Intelligent Scheduling of Distributed Applications
Intelligent Scheduling of Distributed Applications
Intelligent Scheduling of Distributed Applications
Intelligent Scheduling of Distributed Applications
Intelligent Scheduling of Distributed Applications
Intelligent Scheduling of Distributed Applications
Intelligent Scheduling of Distributed Applications
Intelligent Scheduling of Distributed Applications
Intelligent Scheduling of Distributed Applications
Intelligent Scheduling of Distributed Applications
Intelligent Scheduling of Distributed Applications
Co-ordinated Scheduling of Communicating Domains
Co-ordinated Scheduling of Communicating Domains
Co-ordinated Scheduling of Communicating Domains
Co-ordinated Scheduling of Communicating Domains
Multi-processor Scheduling
Multi-processor Scheduling
Outline
Outline
Performance Optimizations for Xen
Performance Optimizations for Xen
Performance Optimizations for Xen
Performance Optimizations for Xen
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Optimizing Network Communication
Outline
Outline
Provisioning a Directional Antenna-based Network
Provisioning a Directional Antenna-based Network
Provisioning a Directional Antenna-based Network
Provisioning a Directional Antenna-based Network
Concluding Remarks
Concluding Remarks

Презентация: «Resource Management in Virtualization-based Data Centers». Автор: Bhuvan Urgaonkar. Файл: «Resource Management in Virtualization-based Data Centers.ppt». Размер zip-архива: 637 КБ.

Resource Management in Virtualization-based Data Centers

содержание презентации «Resource Management in Virtualization-based Data Centers.ppt»
СлайдТекст
1 Resource Management in Virtualization-based Data Centers

Resource Management in Virtualization-based Data Centers

Bhuvan Urgaonkar Computer Systems Laboratory Pennsylvania State University

2 Data Center

Data Center

Cluster of compute and storage servers connected by high-speed network Rent out resources in return for revenue Internet applications, Scientific applications, … Revenue scheme expressed using SLAs

3 Resource Management in Data Centers

Resource Management in Data Centers

Goal: Meet application SLAs Easy solution: Over-provision resources Over-provisioning can be very wasteful Energy, management, failures, … Data center would like to maximize revenue! Dynamic capacity provisioning: match resource allocations to varying workloads Challenges: Determining changing resource needs of applications Effective sharing of resources among applications E.g., server consolidation can reduce cost Automating resource management

4 Resource Management in Data Centers

Resource Management in Data Centers

Goal: Meet application SLAs Easy solution: Over-provision resources Over-provisioning can be very wasteful Energy, management, failures, … Data center would like to maximize revenue! Dynamic capacity provisioning: match resource allocations to varying workloads Challenges: Determining changing resource needs of applications Effective sharing of resources among applications E.g., server consolidation can reduce cost Automating resource management

5 Motivation for Virtualized Hosting in Data Centers

Motivation for Virtualized Hosting in Data Centers

Key idea: Design data center using virtualization Virtual machine monitor (VMM) and virtual machine (VM) A software layer that runs on a server and allows multiple OS/applications to co-exist Each OS/application is given the illusion of its own “virtual” machine that it has to itself Why is this good? Consolidation of diverse OS/apps possible Migration made easier Small code of VMM => improved security Not a new idea, but existing solutions are inadequate Goal: Devise efficient resource management solutions for a virtualization-based data center

6 The Xen Virtual Machine Monitor

The Xen Virtual Machine Monitor

VMM = hypervisor VM = domain Para-virtualization Special domain called Dom0

Dom0

Dom1

Dom2

Apache Web server

Mysql database

Windows’

Linux’

Xen hypervisor

Hardware

7 Outline

Outline

Introduction and Motivation Resource Management in a Xen-based Data Center Resource Accounting Resource Allocation and Scheduling Performance Optimizations for Xen Other Research Concluding Remarks

8 Xen-based Data Center

Xen-based Data Center

Each application component runs within a Xen domain

Online book-store

Online game server

Dom0

Dom0

Dom1

Dom2

Dom1

Dom2

Mysql database

Apache

Quake 1

Mysql

Quake 2

Windows’

Linux’

Windows’

Linux’

Xen hypervisor

Xen hypervisor

Hardware

Hardware

Physical machine # 1

Physical machine # 2

9 Resource Usage Accounting

Resource Usage Accounting

Need for accurate resource accounting Estimate future needs Relate performance and resource consumption Charge applications for resource usage Accounting in Xen-based hosting Statistics for each DomU can be gathered by hypervisor E.g., number of bytes sent by a DomU Hidden activity: CPU activity performed by Dom0 Similar to activity done by a kernel for a process Techniques to de-multiplex Dom0’s activity across DomUs How much work does Dom0 have to do for each DomU?

10 Resource Allocation

Resource Allocation

Multi-time scale resource allocation Server assignment: course time-scale Scheduling: fine time-scale Placement Like a knapsack problem What time-scale? Migration versus replication

11 Intelligent Scheduling of Distributed Applications

Intelligent Scheduling of Distributed Applications

Motivation: Co-scheduling of parallel applications Schedule distributed communicating components together

Physical machine # 1

Physical machine # 2

12 Intelligent Scheduling of Distributed Applications

Intelligent Scheduling of Distributed Applications

Motivation: Co-scheduling of parallel applications Schedule distributed communicating components together

Physical machine # 1

Physical machine # 2

13 Intelligent Scheduling of Distributed Applications

Intelligent Scheduling of Distributed Applications

Motivation: Co-scheduling of parallel applications Schedule distributed communicating components together

Physical machine # 1

Physical machine # 2

14 Intelligent Scheduling of Distributed Applications

Intelligent Scheduling of Distributed Applications

Motivation: Co-scheduling of parallel applications Schedule distributed communicating components together

Physical machine # 1

Physical machine # 2

Message waits till yellow app gets the CPU

15 Intelligent Scheduling of Distributed Applications

Intelligent Scheduling of Distributed Applications

Motivation: Co-scheduling of parallel applications Schedule distributed communicating components together

Physical machine # 1

Physical machine # 2

Message can be received Immediately if the yellow app gets the CPU

16 Intelligent Scheduling of Distributed Applications

Intelligent Scheduling of Distributed Applications

Motivation: Co-scheduling of parallel applications Schedule distributed communicating components together

Physical machine # 1

Physical machine # 2

17 Co-ordinated Scheduling of Communicating Domains

Co-ordinated Scheduling of Communicating Domains

Idea #1: Preferentially schedule a DomU when it receives data Modify Xen CPU scheduler to give higher preference to receiving DomU Important: Also need to ensure that Dom0 gets to run to take care of I/O Scheduler should partition the CPU allocation for a DomU into those for Dom0 and DomU appropriately

18 Co-ordinated Scheduling of Communicating Domains

Co-ordinated Scheduling of Communicating Domains

Idea #2: Try to schedule a sender DomU when it is expected to receive the response An application knows best, but mods undesirable Let the hypervisor learn from past behavior E.g., query responses might be returning in 1-2 seconds Idea #3: Anticipatory CPU scheduling If a domain has sent/received data, it may be likely to do that again E.g., queries may be issued in bursts Trade-off between domain context switch and how much extra time you let a sender DomU continue

19 Multi-processor Scheduling

Multi-processor Scheduling

Idea: Dom0 should be scheduled together with a DomU doing I/O Utilize the multiple CPUs to “co-schedule” a communicating DomU with Dom0 Ensure domains that communicate a lot do not starve others Relaxed fairness: 50% CPU over intervals > 1 second Approach: Decay the CPU priority of communicating DomUs to ensure relaxed fairness is not violated

20 Outline

Outline

Introduction and Motivation Resource Management in a Xen-based Data Center Resource Accounting Resource Allocation and Scheduling Performance Optimizations for Xen Other Research Concluding Remarks

21 Performance Optimizations for Xen

Performance Optimizations for Xen

Switching between native & virtual hosting Dynamic merging and splitting of domains Overbooking of memory Improved migration techniques Coalesce network packets directed to the same physical server

22 Performance Optimizations for Xen

Performance Optimizations for Xen

Switching between native & virtual hosting Dynamic merging and splitting of domains Overbooking of memory Improved migration techniques Coalesce network packets directed to the same physical server

23 Optimizing Network Communication

Optimizing Network Communication

Dom0

Dom0

Dom1

Dom2

Dom1

Dom2

Mysql database

Apache

Quake 1

Mysql

Quake 2

Windows’

Linux’

Windows’

Linux’

Xen hypervisor

Xen hypervisor

Hardware

Hardware

24 Optimizing Network Communication

Optimizing Network Communication

Dom0

Dom0

Dom1

Dom2

Dom1

Dom2

Mysql database

Apache

Quake 1

Mysql

Quake 2

Windows’

Linux’

Windows’

Linux’

Xen hypervisor

Xen hypervisor

Hardware

Hardware

25 Optimizing Network Communication

Optimizing Network Communication

Dom0

Dom0

Dom1

Dom2

Dom1

Dom2

Mysql database

Apache

Quake 1

Mysql

Quake 2

Windows’

Linux’

Windows’

Linux’

Xen hypervisor

Xen hypervisor

Hardware

Hardware

26 Optimizing Network Communication

Optimizing Network Communication

Dom0

Dom0

Dom1

Dom2

Dom1

Dom2

Mysql database

Apache

Quake 1

Mysql

Quake 2

Windows’

Linux’

Windows’

Linux’

Xen hypervisor

Xen hypervisor

Hardware

Hardware

27 Optimizing Network Communication

Optimizing Network Communication

Dom0

Dom0

Dom1

Dom2

Dom1

Dom2

Mysql database

Apache

Quake 1

Mysql

Quake 2

Windows’

Linux’

Windows’

Linux’

Xen hypervisor

Xen hypervisor

Hardware

Hardware

28 Optimizing Network Communication

Optimizing Network Communication

Dom0

Dom0

Dom1

Dom2

Dom1

Dom2

Mysql database

Apache

Quake 1

Mysql

Quake 2

Windows’

Linux’

Windows’

Linux’

Xen hypervisor

Xen hypervisor

Hardware

Hardware

29 Optimizing Network Communication

Optimizing Network Communication

Dom0

Dom0

Dom1

Dom2

Dom1

Dom2

Mysql database

Apache

Quake 1

Mysql

Quake 2

Windows’

Linux’

Windows’

Linux’

Xen hypervisor

Xen hypervisor

Hardware

Hardware

30 Optimizing Network Communication

Optimizing Network Communication

Dom0

Dom0

Dom1

Dom2

Dom1

Dom2

Mysql database

Apache

Quake 1

Mysql

Quake 2

Windows’

Linux’

Windows’

Linux’

Xen hypervisor

Xen hypervisor

Hardware

Hardware

31 Optimizing Network Communication

Optimizing Network Communication

Dom0

Dom0

Dom1

Dom2

Dom1

Dom2

Mysql database

Apache

Quake 1

Mysql

Quake 2

Windows’

Linux’

Windows’

Linux’

Xen hypervisor

Xen hypervisor

Hardware

Hardware

32 Optimizing Network Communication

Optimizing Network Communication

Dom0

Dom0

Dom1

Dom2

Dom1

Dom2

Mysql database

Apache

Quake 1

Mysql

Quake 2

Windows’

Linux’

Windows’

Linux’

Xen hypervisor

Xen hypervisor

Hardware

Hardware

33 Optimizing Network Communication

Optimizing Network Communication

Dom0

Dom0

Dom1

Dom2

Dom1

Dom2

Mysql database

Apache

Quake 1

Mysql

Quake 2

Windows’

Linux’

Windows’

Linux’

Xen hypervisor

Xen hypervisor

Hardware

Hardware

34 Optimizing Network Communication

Optimizing Network Communication

(-) Increased CPU processing for coalescing and splitting packets (+) Reduced interrupt processing at receiver

Dom0

Dom0

Dom1

Dom2

Dom1

Dom2

Mysql database

Apache

Quake 1

Mysql

Quake 2

Windows’

Linux’

Windows’

Linux’

Xen hypervisor

Xen hypervisor

Hardware

Hardware

35 Optimizing Network Communication

Optimizing Network Communication

What kinds of packets can be coalesced? TCP ACKs? Other packets? Would it make sense to do anticipatory packet scheduling at the sender?

Dom0

Dom0

Dom1

Dom2

Dom1

Dom2

Mysql database

Apache

Quake 1

Mysql

Quake 2

Windows’

Linux’

Windows’

Linux’

Xen hypervisor

Xen hypervisor

Hardware

Hardware

36 Outline

Outline

Introduction and Motivation Resource Management in a Xen-based Data Center Resource Accounting Resource Allocation and Scheduling Performance Optimizations for Xen Other Research Concluding Remarks

37 Provisioning a Directional Antenna-based Network

Provisioning a Directional Antenna-based Network

Directional antennas Longer reach Less interference => Increased capacity

38 Provisioning a Directional Antenna-based Network

Provisioning a Directional Antenna-based Network

Theoretical results User-centric version Fair bandwidth allocation Optimal algorithm based on dynamic programming Provider-centric version Maximize revenue NP-hard, 2-approximation algorithm Ongoing work Heuristics to incorporate mobility Evaluation through simulation Implementation … may be

39 Concluding Remarks

Concluding Remarks

Resource mgmt. in virtualized environments Provisioning wireless networks Energy optimization in sensor networks Distributed systems, Operating systems Combination of analysis, algorithm design and experimentation with prototypes Acknowledgements: Faculty: Anand, Piotr, Wang-Chien Students: Amitayu, Arjun, Ross, Shiva, Sriram

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