Free Network Measurement for Adaptive Virtualized Distributed Computing

Ashish Gupta, Marcia Zangrilli, Ananth Sundararaj, Anne Huang, Peter A. Dinda, Bruce B. Lowekamp

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Overview

Benefits of VMs: transparent portability, adaptation, security

Contributions:1. Online passive measurement of

physical layer’s available bandwidth (Wren)

2. Integration of Virtuoso’s application monitoring and Wren’s traffic monitoring

3. Adaptation algorithms that use passive monitoring to solve challenging adaptation problems

Virtual Machines

Virtual Network

PhysicalNetwork

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Adaptive Virtualized Distributed Computing• How can we efficiently utilize resources in a

virtual machine distributed system?– Accurately monitor resource availability– Transparently adapt to changing conditions– Keep application portability simple

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Claim• Virtualization enables the broad application of

dream techniques…– Adaptation– Resource reservation

• … using existing, unmodified applications and operating systems– So everyone can use the techniques

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Optimization of Virtual System Environment

Three Main Components

VNET VTTIF WREN

Layer 2 virtual overlay

networking

Runtime Application Topology Inference

Online Passive bw monitoring and network

characterization

Three Main Components

VNET VTTIF WREN

Layer 2 virtual overlay

networking

Runtime Application Topology Inference

Online Passive bw monitoring and network

characterization

Three Main Components

VNET VTTIF WREN

Layer 2 virtual overlay

networking

Runtime Application Topology Inference

Online Passive bw monitoring and network

characterization

Benefit: Completely independent of application or Operating System

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Outline

• Virtuoso– Overview of distributed VM system– VTTIF– VNET

• Wren– Online Wren overview– Wren performance

• Integration of Virtuoso and Wren• Adaptation

– Algorithms– Results

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Virtuoso

1. Automatically infer application demands (network/CPU)

2. Monitor resource availability (bw/latency/CPU)

3. Adapt distributed application for better performance/cost effectiveness

4. Reserve Resources when possible

Distributed computing environment composed of virtual machines interconnected with virtual networks

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VMLayer

VnetdLayer

PhysicalLayer

Application communicationtopology and traffic load;application processor load

Network bandwidth andlatency; sometimes topology

Vnetd layer can collect all this information as a sideeffect of packet transfersand invisibly act• VM Migration• Topology change• Routing change• Reservation

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Virtual Topology and Traffic Inference Framework (VTTIF) Operation

• Infers application topology and traffic load at runtime

• Resistant to rapid fluctuations and provides damped network view

• All local views aggregated to central proxy to give global view of distributed application

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Virtual Topology and Traffic Inference Framework (VTTIF) Operation

Application topology is recovered using

normalization and pruning algorithms

Ethernet-level traffic monitoring

VNET daemons collectively aggregate

a global traffic matrix for all VMs

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VNET• Virtual overlay network → creates illusion of

LAN over wide area– Network transparency with VM migration– Ideal monitoring point for application monitoring

User

User’s LAN

VM

User

User’s LAN

VM

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Watching Resources from the Edge of the Network (Wren): A Hybrid Monitoring Approach

Wren Design:– Kernel-level instrumentation to collect traces of application traffic.

– Analysis and management of traces handled in user-level.

Wren capabilities:

1. Observes incoming/outgoing packets

2. Online analysis to derive latency/bandwidth information for all host pair connections

3. Answers network queries for any pair of hosts

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Wren Architecture

Linux Kernel

WREN Packet Tracer

WREN Analysis Thread

Grid Application

SOAP Interface

IP

UDP TCP

bw measurements

NetworkLinux Kernel

WREN Packet Tracer

WREN Analysis Thread

Grid Application

SOAP Interface

IP

UDP TCP

bw measurements

Network

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Wren Online Available Bandwidth Algorithm

Applies self-induced congestion principle – If packets are sent at a rate larger than the available bandwidth, the queuing

delays will have an increasing trend.– Find the rate just before queuing delays are incurred

1. Identifies outgoing Maximal length trains with similar spaced packets.

2. Calculates ISR ( Initial Sending Rate ) for these trains.3. Monitors ACK return rate to determine trends in RTTs.4. Increase trend indicates congestion, non increasing trend indicates

lower bound for bw.

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Wren Performance

Key Advantage : WREN accurately reports available bandwidth when application traffic does not saturate the path

Controlled load/latency testbedNistnet → emulate WAN environment with congestionLatency : 20 to 100 ms , bw : 3 to 25 Mbps

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WrenNetworkInference

Host OS Kernel

TCP / UDP Forwarding

Layer 2 Network Interface

VTTIF Application Inference

VADAPT Adaptation

Virtual Machine Monitor

Guest OS Kernel

Application

Virtual Machine

LAN Other VNET daemon

Integrating Virtuoso and Wren

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Adaptation Process

Network Availability

Application Demand

VM to HOST mapping

Provide Overlay Topology

Provide forwarding rules

Network Availability

Application Demand

VM to HOST mapping

Provide Overlay Topology

Provide forwarding rules

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What defines Good Adaptation?

• Various ways to define good adaptation

Current Metric : Maximum residual bottleneck bandwidth

How can we map the processes and paths such that (available bandwidth – demanded bandwidth) is maximized ? Maximum room for performance improvement

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Optimization Problem

• Given the– network traffic load matrix of the application – computational intensity in each VM– topology of the network– load on its links, routers and hosts

• What is the – mapping of VMs to hosts– overlay topology connecting the hosts– forwarding rules on that topology– required CPU and network reservations

• That – maximizes the application performance?

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Problem formulation

Objective function

Application demands

Measured data

Constraints

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Greedy Heuristic

Mapping– Identifies Hosts which have good bandwidth

connectivity and maps VMs over them

Overlay paths– Uses adapted Dijktra to find “widest” paths depending

on bandwidth demands of application process pairs (sorted in decreasing order)

→ finds path which leaves maximum residual bottleneck bandwidth

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Simulated Annealing

Motivation : Search Space is very large → Huge number of possibilities for mapping and overlay paths

Approach1. Start with an initial solution

2. Perturb current configuration and evaluate with a cost function

3. Continue Controlled Perturbation until a good cost function is achieved

Perturbation function and algorithm details in paper

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Experimental Setup• Evaluation conducted in simulation• In each scenario the goal is

– to generate a configuration consisting of VM to Host mappings

– paths between the communicating VMs – Such that the total residual bottleneck bandwidth is

maximized

• We compare – greedy heuristic (GH)– simulated annealing approach (SA) – SA with the GH solution as the starting point (SA+GH). – Additionally we also maintain the best solution found so

far with (SA+GH), i.e. (SA+GH+B), where ’B’ indicates the best solution so far.

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Adaptation ResultsScenario 1 : Only a particular VM to Host mapping yields good performance.

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Scenario 1 Results

• Both Annealing and Greedy perform well.• Annealing advantage : Multi-Constraint optimization

easy

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• Results for Multi Constraint Cost Function : Bandwidth and Latency• Annealing easy to adapt and finds good mappings compared to

heuristic

Scenario 2 : Large 256 host topology. 32 potential hosts, 8 Virtual Machines

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Conclusion

• Network measurements can be provided for free!• These measurements can be used to improve

application performance through adaptation• Virtuoso and Wren Integrated system

– Low overhead – Provides application and resource measurements– Allows transparent optimization of application performance

• Adaptation Strategies– Greedy heuristic and simulated annealing approaches are able

to find good mappings/configurations

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• Please visit– Prescience Lab (Northwestern University)

• http://plab.cs.northwestern.edu

– Wren: Watching Resources fro the Edge of the Network (William and Mary)• http://www.cs.wm.edu/~lowekamp/wren.html

– Virtuoso: Resource Management and Prediction for Distributed Computing using Virtual Machines

• http://virtuoso.cs.northwestern.edu• VNET is publicly available from above URL

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