Smart Cloud Federation Simulations with CloudSim Gaetano F. - - PowerPoint PPT Presentation

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Smart Cloud Federation Simulations with CloudSim

Gaetano F. Anastasi, Emanuele Carlini, Patrizio Dazzi

Contrail is co-funded by the EC 7th Framework Programme under Grant agreement nr. 257438

National Research Council of Italy

Clouds are spreading...

• Several different Cloud Providers and Technologies
• providing very different kind of resources both from the

point of view of:

✤

Abstraction

✤

Features

✤

Usage model

• Adoption in different sectors
• Towards a real market of Clouds

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...but are current Clouds issue-free ?

• Some Cloud Provides could provide
• nly specialized resources
• Who is cheaper for some resources

could be expensive for others

• Cloud Providers could be located only in one

(or just a few) country

• User lock-in issue in Clouds

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How to solve ?

• A Need for Super-entities seamlessly managing

several Cloud Providers

• Federation of Clouds is a potential

solution

• The Contrail approach to Cloud Federations
• Resource Allocation in Cloud Federations is important
• Testing it could be not very simple

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Simulate to Test Solutions

• Estensively test different allocation solutions in

“real” Cloud Federation is complex and expensive

• Several possible environments / technologies
• Different kinds of applications
• $$$ it costs money $$$
• Simulators are part of the solution

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What do we want to simulate in a Federation ?

• Different Kinds of
• Applications

✤

inter-arrival

✤

constraints

• Clouds

✤

Resources

✤

Cost Models

• Different Strategies for
• Monitoring
• Allocation

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What did we do ?

• A model for describing Cloud

Federations

• An extension to CloudSim

addressing Contrail like Cloud Federations

• Validated our approach conducting some tests

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The Cloud Federation Model

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How we model Cloud Federations

• Application Model
• Resource Model
• Application Queue Model
• Resource Monitoring Model
• Resource Allocation Model

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Application Model

• Graph-based Representation
• Node = Appliance
• Edge = Information Exchange
• Functional Requirements
• SLA Terms
• Network Requirements

CPU = ... RAM = ... SLA terms = ... N/W Bandwidth = ...

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Resource Model

• Organized in Datacenters
• IaaS resources
• Presented as VM slots
• Internet Estimator for modeling interconnections

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Application Queue Model

• Models the arrival of Applications
• Inter-arrival time
• Information provided

✤ e.g. amount, quality, ...

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Resource Monitoring Model

• Amount and Quality of information about

resources availability

• Update frequency
• Aggregation style

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Resource Allocation Model

• Association of Resources to Applications
• Appliance by Appliance
• Allocation Matrix
• ci,j means:

✤

j-th datacenter able to run the i-th appliance

• Computed using both static and dynamic

information

trix Y =    c1,1 · · · c1,P . . . ... . . . cN,1 · · · cN,P    where the element c re

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The CloudSim Extension

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SmartFed Simulator

• Built on top of CloudSim exploiting its:
• Datacenter
• Broker
• CloudLet
• CloudSim proven to be well-conceived for

reusing and flexibility

• Why we had to add something ?

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What is missing in CloudSim ?

• Datacenters characterization with

non-functional features,

• e.g. reputation estimation
• Brokers with complex allocation strategies
• integrated with the whole SmartFed eco-system
• CloudLets characterized by explicit relationships with
• ther CloudLets

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SmartFed Eco-System

• Application
• Application Queue
• Internet Estimator
• Monitoring Hub
• Allocator

SmartFed CloudSim

Storage Monitoring Reputation Federation Datacenter SLA Application Application Vertex Application Edge Queue Allocator allocate

<<use>> <<use>> <<use>> <<use>> <<use>> <<use>> <<use>> <<use>> <<use>> <<use>> <<use>>

Broker Datacenter CloudLet

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The Validation of the Approach

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Hands on SmartFed

• Validation of SmartFed
• A sample, very classic application
• Different sizes of applications and

datacenters

• Very simple allocation algorithm

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A sample Application

• Three-tier applications
• Web front-end
• Business logic
• Database
• 10, 100 and 1000

appliances per application

Web Frontend (Presentation tier)

RAM 2 Ghz CPU type 2 x64 2 GB CPU Freq. Cores

ApplicationServer (Business logic tier) Database (Persistency tier)

1024 Kb/s Security 1000 ms Latency SSL Bandwidth RAM 3 Ghz CPU type 4 x64 16 GB CPU Freq. Cores 512 Kb/s Security 1000 ms Latency SSL Bandwidth RAM 2 Ghz CPU type 2 x64 4 GB CPU Freq. Cores

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Machines distribution into Clouds (Datacenter entities)

• Two different kind of distributions
• Uniform:

✤

each datacenter owns the same number of machines

✤

each datacenter has enough machines to run an instance of the application

• Normal:

✤

the # of machines in each datacenter follows a normal distribution

✤

some datacenters are not be able to host the application

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Allocation Algorithm

• When the Application is received:
• is decomposed in its VMs
• a Datacenter d is chosen randomly

among the ones able to run one or more VMs

• If d has enough room is chosen
• When d is full, another datacenter is chosen
• When all the VMs have been assigned, it terminates

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Experimental Results

                         

10 Datacenters 100 Datacenters

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Conclusions

• Modeling of application and cloud resources

targeting (Federation of) Cloud platforms

• Contrail in particular but a pretty general approach
• Enhriched CloudSim to support
• more complex SLA model
• mechanisms to support off-line mapping of applications
• Validation of the solution

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Future Works

• Extensive validation
• testing different allocation strategies
• validation against different Cloud Simulators

✤

e.g. iCanCloud

• Exploiting different kind of applications and resources
• possibly using information about real ones
• Integration of Security Aspects
• Enhanced Modeling of Queues
• e.g. with Markov models

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Acknowledgements

Funded under: FP7 (Seventh Framework Programme) Area: Internet of Services, Software & Virtualization (ICT

• 2009.1.2)

Project reference: 257438 Total cost: 11,29 million euro EU contribution: 8,3 million euro Execution: From 2010-10-01 untill 2013-09-30 Duration: 36 months Contract type: Collaborative project (generic)

contrail is co-funded by the

EC 7th Framework Programme

http://contrail-project.eu

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Questions ?