Ananth I. Sundararaj Ashish Gupta Peter A. Dinda Prescience Lab

Slides:



Advertisements
Similar presentations
All Rights Reserved © Alcatel-Lucent 2009 Enhancing Dynamic Cloud-based Services using Network Virtualization F. Hao, T.V. Lakshman, Sarit Mukherjee, H.
Advertisements

1 Scoped and Approximate Queries in a Relational Grid Information Service Dong Lu, Peter A. Dinda, Jason A. Skicewicz Prescience Lab, Dept. of Computer.
© 2007 Cisco Systems, Inc. All rights reserved.Cisco Public 1 Version 4.0 Communicating over the Network Network Fundamentals – Chapter 2.
1 Virtual Machine Resource Monitoring and Networking of Virtual Machines Ananth I. Sundararaj Department of Computer Science Northwestern University July.
Towards Virtual Networks for Virtual Machine Grid Computing Ananth I. Sundararaj Peter A. Dinda Prescience Lab Department of Computer Science Northwestern.
Automatic Run-time Adaptation in Virtual Execution Environments Ananth I. Sundararaj Advisor: Peter A. Dinda Prescience Lab Department of Computer Science.
Increasing Application Performance In Virtual Environments Through Run-time Inference and Adaptation Ananth I. Sundararaj Ashish Gupta Peter A. Dinda Prescience.
Increasing Application Performance In Virtual Environments Through Run-time Inference and Adaptation Ananth I. Sundararaj Ashish Gupta Peter A. Dinda Prescience.
Security Awareness: Applying Practical Security in Your World, Second Edition Chapter 5 Network Security.
Ashish Gupta, Marcia Zangrilli, Ananth I. Sundararaj, Peter A. Dinda, Bruce B. Lowekamp EECS, Northwestern University Computer Science, College of William.
Dynamic Topology Adaptation of Virtual Networks of Virtual Machines Ananth I. Sundararaj Ashish Gupta Peter A. Dinda Prescience Lab Department of Computer.
Hardness of Approximation and Greedy Algorithms for the Adaptation Problem in Virtual Environments Ananth I. Sundararaj, Manan Sanghi, John R. Lange and.
An Optimization Problem in Adaptive Virtual Environments Ananth I. Sundararaj Manan Sanghi Jack R. Lange Peter A. Dinda Prescience Lab Department of Computer.
Inferring the Topology and Traffic Load of Parallel Programs in a VM environment Ashish Gupta Resource Virtualization Winter Quarter Project.
1 Automatic Dynamic Run-time Optical Network Reservations John R. Lange Ananth I. Sundararaj and Peter A. Dinda Prescience Lab Department of Computer Science.
Towards Virtual Networks for Virtual Machine Grid Computing Ananth I. Sundararaj Peter A. Dinda Prescience Lab Department of Computer Science Northwestern.
The Whats and Whys of Whole System Virtualization Peter A. Dinda Prescience Lab Department of Computer Science Northwestern University
Adaptive Virtual Networking For Virtual Machine-based Distributed Computing Peter A. Dinda Prescience Lab Department of Computer Science Northwestern University.
Free Network Measurement for Adaptive Virtualized Distributed Computing Ashish Gupta, Marcia Zangrilli, Ananth Sundararaj, Anne Huang, Peter A. Dinda,
Dynamic Topology Adaptation of Virtual Networks of Virtual Machines Ananth I. Sundararaj Ashish Gupta Peter A. Dinda Prescience Lab Department of Computer.
Inferring the Topology and Traffic Load of Parallel Programs in a VM environment Ashish Gupta Peter Dinda Department of Computer Science Northwestern University.
1 25\10\2010 Unit-V Connecting LANs Unit – 5 Connecting DevicesConnecting Devices Backbone NetworksBackbone Networks Virtual LANsVirtual LANs.
© 2007 Cisco Systems, Inc. All rights reserved.ICND1 v1.0—4-1 LAN Connections Exploring the Functions of Routing.
© 2007 Cisco Systems, Inc. All rights reserved.Cisco Public 1 Version 4.0 Communicating over the Network Network Fundamentals – Chapter 2.
Connecting LANs, Backbone Networks, and Virtual LANs
CECS 474 Computer Network Interoperability WAN Technologies & Routing
Data Center Network Redesign using SDN
Chapter 2 The Infrastructure. Copyright © 2003, Addison Wesley Understand the structure & elements As a business student, it is important that you understand.
Department of Computer Science Engineering SRM University
Wave Relay System and General Project Details. Wave Relay System Provides seamless multi-hop connectivity Operates at layer 2 of networking stack Seamless.
Hands-On Virtual Computing
GrIDS -- A Graph Based Intrusion Detection System For Large Networks Paper by S. Staniford-Chen et. al.
Software-Defined Networks Jennifer Rexford Princeton University.
Common Devices Used In Computer Networks
Repeaters and Hubs Repeaters: simplest type of connectivity devices that regenerate a digital signal Operate in Physical layer Cannot improve or correct.
EmNet: Satisfying The Individual User Through Empathic Home Networks J. Scott Miller, John R. Lange & Peter A. Dinda Department of Electrical Engineering.
Chapter 2 Network Topology
Introduction to OSPF Nishal Goburdhan. Routing and Forwarding Routing is not the same as Forwarding Routing is the building of maps Each routing protocol.
Summary - Part 2 - Objectives The purpose of this basic IP technology training is to explain video over IP network. This training describes how video can.
NET 324 D Networks and Communication Department Lec1 : Network Devices.
McGraw-Hill©The McGraw-Hill Companies, Inc., 2004 Connecting Devices CORPORATE INSTITUTE OF SCIENCE & TECHNOLOGY, BHOPAL Department of Electronics and.
Virtual Machines Created within the Virtualization layer, such as a hypervisor Shares the physical computer's CPU, hard disk, memory, and network interfaces.
20409A 7: Installing and Configuring System Center 2012 R2 Virtual Machine Manager Module 7 Installing and Configuring System Center 2012 R2 Virtual.
11 ROUTING IP Chapter 3. Chapter 3: ROUTING IP2 CHAPTER INTRODUCTION  Understand the function of a router.  Understand the structure of a routing table.
Network Virtualization Ben Pfaff Nicira Networks, Inc.
Chapter 3 Part 1 Switching and Bridging
DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING CLOUD COMPUTING
Bentley Systems, Incorporated
Connecting LANs, Backbone Networks
Computer Networking Devices
VIRTUAL SERVERS Presented By: Ravi Joshi IV Year (IT)
Troubleshooting IP Addressing
Northwestern Lab for Internet and Security Technology (LIST) Yan Chen Department of Computer Science Northwestern University.
Grid Information Services: alternate models
GGF15 – Grids and Network Virtualization
Aled Edwards, Anna Fischer, Antonio Lain HP Labs
Virtualization, Empathic Systems, and Sensors
HWP2 – Distributed search
湖南大学-信息科学与工程学院-计算机与科学系
Network Virtualization
20409A 7: Installing and Configuring System Center 2012 R2 Virtual Machine Manager Module 7 Installing and Configuring System Center 2012 R2 Virtual.
Department of Computer Science Northwestern University
IS4680 Security Auditing for Compliance
Firewalls Routers, Switches, Hubs VPNs
OPS235: Configuring a Network Using Virtual Machines – Part 2
70-293: MCSE Guide to Planning a Microsoft Windows Server 2003 Network, Enhanced Chapter 4: Planning and Configuring Routing and Switching.
Potentially Interesting Startup and/or Commercialization Opportunities
How To Configure Hotspot in Virtual Mikrotik on VMware
An Optimization Problem in Adaptive Virtual Environments
COMPUTER NETWORKS CS610 Lecture-16 Hammad Khalid Khan.
Presentation transcript:

Increasing Application Performance In Virtual Environments Through Run-time Inference and Adaptation Ananth I. Sundararaj Ashish Gupta Peter A. Dinda Prescience Lab Department of Computer Science Northwestern University http://virtuoso.cs.northwestern.edu

Summary Dynamically adapt unmodified applications on unmodified operating systems in virtual environments to available resources The adaptation mechanisms are application independent and controlled automatically without user or developer help Demonstrate the feasibility of adaptation at the level of collection of VMs connected by Virtual Networks Show that its benefits can be significant for two classes of applications

Outline Virtual machine grid computing Virtuoso system Networking challenges in Virtuoso Enter VNET VNET, VTTIF Adaptive virtual network Evaluation Summary

Virtual Machines What are they? Virtual Machine Grid Computing Aim Deliver arbitrary amounts of computational power to perform distributed and parallel computations 1 Traditional Paradigm New Paradigm 2 5 Grid Computing using virtual machines Resource multiplexing using OS level mechanism Grid Computing 4 3a 3b 6a Problem1: 6b Virtual Machines What are they? Complexity from resource user’s perspective Solution Problem2: How to leverage them? Complexity from resource owner’s perspective

Virtual Machines Virtual machine monitors (VMMs) Raw machine is the abstraction VM represented by a single image VMware GSX Server

The Simplified Virtuoso Model Virtual networking ties the machine back to user’s home network User’s LAN Specific hardware and performance VM Basic software installation available Orders a raw machine Virtuoso continuously monitors and adapts User

User’s View in Virtuoso Model User’s LAN VM User

Outline Virtual machine grid computing Virtuoso system Networking challenges in Virtuoso Enter VNET VNET, VTTIF Adaptive virtual network Evaluation Summary

VNET: A bridge with long wires Virtual Networks VM traffic going out on foreign LAN Foreign hostile LAN X User’s friendly LAN IP network Virtual Machine Host A machine is suddenly plugged into a foreign network. What happens? Does it get an IP address? Is it a routeable address? Does firewall let its traffic through? To any port? Proxy VNET: A bridge with long wires

A VNET Link Ethernet Packet Captured by Interface in Promiscuous mode First link Second link (to proxy) “Host Only” Network VM 1 VM 2 “eth0” “eth0” ethy ethz vmnet0 vmnet0 VNET IP Network VNET Ethernet Packet Tunneled over TCP/SSL Connection Host Host Ethernet Packet is Matched against the Forwarding Table on that VNET Ethernet Packet is Matched against the Forwarding Table on that VNET Local traffic matrix inferred by VTTIF Periodically sent to the VNET on the Proxy

Virtual Topology and Traffic Inference Framework (VTTIF) Operation Ethernet-level traffic monitoring VNET daemons collectively aggregate a global traffic matrix for all VMs Explain the visualization generated. Finally a one step process: Doitall [parallel program name] and it went through all the steps and displayed the infered topology Add: pvmpov running Application topology is recovered using normalization and pruning algorithms

Dynamic Topology Inference by VTTIF VNET Daemons on Hosts Aggregated Traffic Matrix VNET Daemon at Proxy Smoothed Traffic Matrix 2. Low Pass Filter Aggregation 1. Fast updates 3. Threshold change detection Topology change output

Outline Virtual machine grid computing Virtuoso system Networking challenges in Virtuoso Enter VNET VNET, VTTIF Adaptive virtual network Evaluation Summary

Adaptation Applications Application performance measure BSP Transactional ecommerce Application performance measure Application throughput VTTIF Network monitoring Monitoring and inference Single hop Worst fit Optimization metric Single metric Combined metric Adaptation algorithm Overlay topology Forwarding rules VM migration Adaptation mechanisms

Optimization Problem (1/2) Topology Only Informally stated: Input Network traffic load matrix of application Output Overlay topology connecting hosts Forwarding rules on the topology Such that the application throughput is maximized The algorithm is described in detail in the paper

Illustration of Topology Adaptation in Virtuoso Fast-path links amongst the VNETs hosting VMs Resilient Star Backbone User’s LAN Foreign host LAN 1 VM 1 Host 1 + VNET IP network Proxy + VNET Merged matrix as inferred by VTTIF Foreign host LAN 2 VM 2 VM 4 VM 3 Host 3 + VNET Host 4 + VNET Host 2 + VNET Foreign host LAN 4 Foreign host LAN 3

Evaluation Wide-Area testbed Reaction time of VNET Patterns: A synthetic BSP benchmark Benefits of adaptation (performance speedup) Eight VMs on a single cluster, all-all topology Eight VMs spread over WAN, all-all topology Wide-Area testbed DOT Network CMU Northwestern VM 6 Proxy VM 8 University of Chicago VM 5 … VM 1 VM 7

Reaction Time

Benefits of Adaptation Benefits accrued as a function of the number of fast-path links added Patterns has an all-all topology Eight VMs are used All VMs are hosted on the same cluster

Benefits of Adaptation Benefits accrued as a function of the number of fast-path links added Patterns has an all-all topology Eight VMs are used VMs are spread over WAN

Optimization Problem (2/2) Topology + Migration Informally stated: Input Network traffic load matrix of application Topology of the network Output Mapping of VMs to hosts Overlay topology connecting hosts Forwarding rules on the topology Such that the application throughput is maximized The algorithm is described in detail in the paper

Evaluation Applications Benefits of adaptation (performance speedup) Patterns: A synthetic BSP benchmark TPC-W: Transactional web ecommerce benchmark Benefits of adaptation (performance speedup) Adapting to compute/communicate ratio Adapting to external load imbalance

Effect on BSP Application Throughput of Adapting to Compute/Communicate Ratio

Effect on BSP Application Throughput of Adapting to External Load Imbalance

TPCW Throughput (WIPS) With Image Server Facing External Load No Topology Topology No Migration 1.216 1.76 Migration 1.4 2.52

Outline Virtual machine grid computing Virtuoso system Networking challenges in Virtuoso Enter VNET VNET, VTTIF Adaptive virtual network Evaluation Summary

Summary Dynamically adapt unmodified applications on unmodified operating systems in virtual environments to available resources The adaptation mechanisms are application independent and controlled automatically without user or developer help Demonstrate the feasibility of adaptation at the level of collection of VMs connected by Virtual Networks Show that its benefits can be significant for two classes of applications

For More Information Future Work Related Talk at HPDC 2005 Free network measurement (Wren) – Collaboration with CS, W&M Applicability of a single optimization scheme Related Talk at HPDC 2005 J. Lange, A. Sundararaj, P. Dinda, “Automatic Dynamic Run-time Optical Network Reservations” Wednesday, July 27, 2:00 P.M. Please visit Prescience Lab (Northwestern University) http://plab.cs.northwestern.edu Virtuoso: Resource Management and Prediction for Distributed Computing using Virtual Machines http://virtuoso.cs.northwestern.edu VNET is publicly available from above URL