Impact of server dynamic allocation on the response time for - - PowerPoint PPT Presentation

Impact of server dynamic allocation

• n the response time for

energy-efficient virtualized web clusters energy-efficient virtualized web clusters

Carlos Oliveira, Vinicius Petrucci, Orlando Loques

{cjunior, vpetrucci, loques} @ic.uff.br

Universidade Federal Fuminense (UFF) Niteroi, Rio de Janeiro, Brazil

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Agenda

• Introduction
• Our work
• Virtualized cluster architecture
• Experiments
• Experiments

– Live migration – Replication

• Conclusion and ongoing work

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Introduction

• Energy consumption – Current context

– Data center, web servers – High demands for energy – Global warming

• What is server virtualization?
• What is server virtualization?

– Server associated to VMs, not to physical machines

• Why adopt server virtualization?

– On-demand allocation – Smaller number of servers – Increase resource utilization – Reduce the use of computer resources and the associated (electrical) power consumption

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Our work

• Issues

– Service disruption on the course of migration – How to allocate VMs in a cluster

• How to solve or reduce them?

– We aim to investigate replication to reduce this disruption

• This work aims to

– Analyze the disruptive impact during dynamic server alocation – Compare migration’s (cold and live) disruption to replication disruption

• We performed a set of experiments to achieve our goal

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Virtualized cluster architecture

The VM Manager is implemented using the OpenNebula toolkit which enables the management of the VMs in the cluster, such as deployment and monitoring deployment and monitoring

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Virtualized cluster architecture

The VM Manager is implemented using the OpenNebula toolkit which enables the management of the VMs in the cluster, such as deployment and monitoring The Load Balancer implements a weighted round-robin scheduler strategy provided by Apache deployment and monitoring

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Virtualized cluster architecture

The VM Manager is implemented using the OpenNebula toolkit which enables the management of the VMs in the cluster, such as deployment and monitoring The Load Balancer implements a weighted round-robin scheduler strategy provided by Apache The Optimizer is designed to monitor and configure the virtualized cluster deployment and monitoring

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Virtualized cluster architecture

We used Xen as the virtual machine hypervisor and Apache servers for running the web applications

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Response time monitoring

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• When CPU utilization of an app is low, the response time is also low
• When utilization is high, the response time abruptly goes up

Live Migration

• Goal: To move a VM to another physical machine

– But maintaining an acceptable QoS (app response time) during this movement

• The disruptions, observed during dynamic changes in live migration, last a short

time and are basically unavoidable because cache contents are not migrated

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Alternative: Replication

• Idea: To create and deploy a new VM replica for the app on

the destination server

• When the new replica is ready (already booted) for processing

the client requests, we start redirecting the requests to this the client requests, we start redirecting the requests to this new replica

• The goal is to evaluate the response time impact compared to

the live migration

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Replication execution

• Replication shows improvements compared to the live migration
• We noticed that if all the current requests were abruptly redirected to the new VM

replica it would take a long time to get both, throughput and response time, stable

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Live migration vs Replication

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Live Migration Replication

Live migration vs Replication

Minor disruption compared to migration

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300 ms 22 ms

Live Migration Replication

Conclusion

• Our goal was to carry out experiments to evaluate the

performance impact in terms of response time and throughput of applications during the course of VM migration and replication

• Our results showed that by using replication we can reduce

performance disruptions incurred during migration

• This evaluation work will help us to implement our overall
• ptimization approach for virtualized clusters (Petrucci et al.

2010)

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Ongoing work

• Include energy savings and response time control in our

experiments

• Experiments with state-aware applications (database tier)

– RuBis (benchmark application – simulates an eBay site) – RuBis (benchmark application – simulates an eBay site)

• Improvements in the dynamic allocation (replication) scheme

– Keep the application on the source server too for load balancing (and fault tolerance) proposes – Identify what part of the application workload would be allocated both in the source and target physical machines

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Thank you!

Our webpage: www.tempo.uff.br

Tempo Lab UFF

The contemporary Art museum in Niteroi, Rio de Janeiro

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Experiments

• We have measured the maximum number of requests per

second that our physical machines can handle

• We used State-less requests

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Response time measurement

• The response time is defined by the difference between the

time a response is generated and the moment the server has accepted the associated request

• To obtain the response time for the web applications we have

implemented a new Apache module that collects the time implemented a new Apache module that collects the time information between these two moments

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Cold Migration

• Cannot be used in Real Time Systems because

it stops

• We have made an experiment in this scenario
• nly to show it
• nly to show it

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Replication (Details)

• (1) booting a new VM replica
• (2) redirecting the requests to the new replica
• The time needed to boot a VM is in between 25 and 40

seconds seconds

• We may also boot the new replica on the target machine a

few seconds earlier to have it running and ready at the moment necessary for using the replicated VM

• In this experiment, we redirected 10% of the requests each

time, until 100% of the requests were redirected to the VM replica

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Testbed

Processor Memory Camburi Intel Pentium 4 2.80GHz 1GB RAM Cumulus Intel Pentium 4 2.80GHz 1GB RAM Henry AMD Athlon 64 3500+ 3GB RAM Maxwell Intel Core i5 2.67GHz 8GB RAM Edison Intel Core i7 CPU 2.67GHz 8GB RAM

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Server virtualization

• Server virtualization allows for on-demand allocation (using

either migration or replication) of virtual machines (VMs), which run the web applications and services, to physical servers

• We have measured and analyzed the disruptive impact on the
• We have measured and analyzed the disruptive impact on the

QoS (quality-of-service) provided by the applications, in terms

• f server-side response time and throughput, during dynamic

allocation of virtual machines in a server cluster

• We have used Xen as the virtual machine manager and

Apache servers for running the web applications

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Xen hypervisor

• The Xen hypervisor offers two kinds of migration: cold and live
• migration. The difference between them is that on cold

migration the VM stops running during migration

• The live migration stages are listed below:
• Cold migration doesn’t have stage 2 presented in the figure

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