market-oriented cloud computing: vision, hype, and reality for delivering it services as computing...
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Market-Oriented Cloud Computing:Vision, Hype, and Reality for Delivering IT
Services as Computing Utilities
Rajkumar Buyya(1,2), Chee Shin Yeo(1), and Srikumar Venugopa(l)
1.Grid Computing and Distributed Systems (GRIDS) Laboratory Department of computer Science and Software Engineering
The University of Melbourne, Australia
2.Manjrasoft Pty Ltd, Melbourne, Australia
HPCC '08. 10th IEEE
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Outline Introduction Market-Oriented Cloud Architecture Commercial offering of market-oriented Clouds
requirement and Qos issue Emerging cloud platform Amazon EC2 intro&pricing Google App Engine intro&pricing Microsoft Anzure platform intro&pricing Possible pricing strategy(by Ming Lung) Conclusions&comments
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Introduction:definition Definition of cloud:
A Cloud is a type of parallel and distributed system;
Consisting of a collection of interconnected and virtualized computers That are dynamically provisioned and presented as
one or more unified computing resources ,based on service-level agreements established
through negotiation between the service provider and consumers.”
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Introduction:trend Web Search Trends:
[C]. Google and Salesforce.com in Cloud computing deal, Siliconrepublic.com - Apr 14 2008
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Market-Oriented Cloud Architecture Cloud providers will need to consider and
meet different QoS parameters of each individual consumer as negotiated in specific SLAs.
Traditional system-centric resource management architecture are no longer fit Do not provide incentives for them to share
their resources. Regard all service requests to be of equal
importance.
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Market-Oriented Cloud Architecture
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Market-Oriented Cloud Architecture
Pricing: The Pricing mechanism decides how service
requests are charged. Ex. submission time (peak/off-peak)
, pricing rates (fixed/changing) Accounting:
Maintains the actual usage of resources by requests and historical information usage. Final cost to charge users. Improve resource allocation decisions.
Service Request Examiner and Admission Control: Interprets the submitted request for QoS requirements
before determining whether to accept or reject the request.
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Market-Oriented Cloud Architecture
Dispatcher: starts the execution of accepted service
requests on allocated VMs. Service Request Monitor:
keeps track of the execution progress of service requests.
VM monitor: Keep track of the availability of VMs and their
resource entitlements.
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Qos parameter issue In cloud there are critical QoS parameters to
consider in a service request time, cost, reliability and trust/security.
In particular, QoS requirements cannot be static and need to be dynamically updated over time. Due to continuing changes in business
operations and operating environments. But , there are no or limited support for
dynamic negotiation of SLAs. Recently, we have developed negotiation
mechanisms based on alternate offers protocol for establishing SLAs [8].
[8]S. Venugopal, X. Chu, and R. Buyya. using the Alternate Offers Protocol (IWQoS 2008), A Negotiation Mechanism for Advance Resource Reservation
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Commercial offering of market-oriented Clouds requirement Customizable
Support customer-driven service management based on customer profiles and requested service requirements.
Market-based resource management Contain computational risk management to
sustain SLA-oriented resource allocation. Incorporate autonomic resource
management models: Effectively self-manage changes in service
requirements to satisfy both new service demands and existing service obligations.
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Emerging cloud platform
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Amazon EC2
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Amazon EC2 Instances Types (Memory / *ECU / Storage /
Platform) Standard Instances
Small (default): 1.7 GB / 1 / 160 GB / 32-bit Large: 7.5 GB / 4 / 850 GB / 64-bit Extra Large: 15 GB / 8 / 1690 GB / 64-bit
High-Memory Instances Double Extra Large: 34.2 GB / 13 / 850 GB / 64-bit Quadruple Extra Large: 68.4 GB / 26 / 1690 GB / 64-bit
High-CPU Instances Medium: 1.7 GB / 5 / 350 GB / 32-bit Extra Large: 7 GB / 20 / 1690 GB / 64-bit
http://aws.amazon.com/ec2/
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About Measuring Compute Resources(quote from Amazon)
*ECU – EC2 Compute Unit, providing the equivalent CPU capacity of a 1.0 – 1.2 GHz 2007 Opteron or 2007 Xeon processor
“Amazon EC2 uses a variety of measures to provide each instance with a consistent and predictable amount of CPU capacity.” We use several benchmarks and tests to manage the
consistency and predictability of the performance of an EC2 Compute Unit.
Over time, we may add or substitute measures that go into the definition of an EC2 Compute Unit, if we find metrics that will give you a clearer picture of compute capacity.
“To find out which instance will work best for your application, the best thing to do is to launch an instance and benchmark your own application.” pay by the hour
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On-Demand Instances
US – N. Virginia EU – Ireland
Standard Instances Linux/UNIX Windows Linux/UNIX Windows
Small (default) $0.085 $0.12 $0.095 $0.13
Large $0.34 $0.48 $0.38 $0.52
Extra Large $0.68 $0.96 $0.76 $1.04
High-Memory Instances
Linux/UNIX Windows Linux/UNIX Windows
Double Extra Large $1.20 $1.44 $1.34 $1.58
Quadruple Extra Large $2.40 $2.88 $2.68 $3.16
High-CPU Instances Linux/UNIX Windows Linux/UNIX Windows
Medium $0.17 $0.29 $0.19 $0.31
Extra Large $0.68 $1.16 $0.76 $1.24Unit: Per Hour
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Reserved InstancesLinux/UNIX One-time fee US – N.
VirginiaUS – N. California & EU – Ireland
Standard Instances 1 yr 3 yr Usage ( /hr)
Usage ( /hr)
Small (default) $227.50
$350 $0.03 $0.04
Large $910 $1400 $0.12 $0.16
Extra Large $1820 $2800 $0.24 $0.32
High-Memory Instances
1 yr 3 yr Usage ( /hr)
Usage ( /hr)
Double Extra Large $3185 $4900 $0.42 $0.56
Quadruple Extra Large $6370 $9800 $0.84 $1.12
High-CPU Instances 1 yr 3 yr Usage ( /hr)
Usage ( /hr)
Medium $455 $700 $0.06 $0.08
Extra Large $1820 $2800 $0.24 $0.32
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Spot Instances Spot Instances enable you to bid for unused Amazon EC2 capacity. To use Spot Instances, you should set
(instance type, region, amount, maximum price)
US – N. Virginia EU – Ireland
Standard Instances Linux/UNIX Windows Linux/UNIX Windows
Small (default) $0.085 $0.12 $0.095 $0.13
Large $0.34 $0.48 $0.38 $0.52
Extra Large $0.68 $0.96 $0.76 $1.04
High-Memory Instances
Linux/UNIX Windows Linux/UNIX Windows
Double Extra Large $1.20 $1.44 $1.34 $1.58
Quadruple Extra Large $2.40 $2.88 $2.68 $3.16
High-CPU Instances Linux/UNIX Windows Linux/UNIX Windows
Medium $0.17 $0.29 $0.19 $0.31
Extra Large $0.68 $1.16 $0.76 $1.24*fluctuates periodically depending on the supply of and demand for Spot Instance
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Data TransferInternet Data Transfer
Data Transfer In
All Data Transfer Free through June 30, 2010*
Data Transfer Out
First 10 TB per Month $0.17 per GB
Next 40 TB per Month $0.13 per GB
Next 100 TB per Month $0.11 per GB
Over 150 TB per Month $0.10 per GB
Data transferred between two Amazon Web Services within the same zone is free of charge.Data transferred between AWS services in same regions but different zone will be charged $0.01 per GB in/out.
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Amazon add-on services Amazon Elastic Block Store
Amazon EBS volumes provide off-instance storage that persists independently from the life of an instance.
Charged per GB/month and I/O request Amazon CloudWatch (bundle with Auto Scaling)
Amazon CloudWatch is a web service that provides monitoring for AWS cloud resources. such as CPU utilization, disk reads and writes, and network traffic.
Auto Scaling allows you to automatically scale your Amazon EC2 capacity up or down according to conditions you define.
Charged per instance-hour Elastic Load Balancing
Elastic Load Balancing automatically distributes incoming application traffic across multiple Amazon EC2 instances.
Charged per hour and GB of data processed
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Google App Engine
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Google App Engine Run web applications on Google’s
infrastructure Programming language support: python, java Pricing:
Quota Fixed quota (for free)
Disable billing Enable billing
Billable quota Budget
http://code.google.com/intl/en/appengine/docs/whatisgoogleappengine.html
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Requests
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Datastore
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URL Fetch
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Image Manipulation
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Memcache
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Billable Quota Unit Cost
http://code.google.com/intl/en/appengine/docs/billing.html
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Microsoft Windows Azure
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Microsoft Windows Azure Windows Azure platform
Provides a scalable environment with compute, storage, hosting, and management capabilities.
SQL Azure A Relational Database for the
Cloud(Windows Azure platform).
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Microsoft Windows Azure During Community Technology Preview (CTP),
services included in Windows Azure will be available without charge Total compute usage: 2000 VM hours/month Cloud storage capacity: 50GB Total storage data transfers: 20GB/day
Once launched for commercial use, Windows Azure would be priced and licensed Jan 1, 2010 First month without charge
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Pricing unit Compute Instances:
(Instance Size, CPU, Memory, Storage, I/O Performance )Small --------1.6 GHz ,1.75 GB, 225 GB, ModerateMedium --2 x 1.6 GHz , 3.5 GB, 490 GB, HighLarge----- 4 x 1.6 GHz, 7 GB, 1,000 GB, HighExtra large-8 x 1.6 GHz, 14 GB, 2,040 GB, High
Instance hour transformation: Instance Size Elapsed Hour Small Instance
Hours Small 1 hour 1 hourMedium 1 hour 2 hours Large 1 hour 4 hours Extra large 1 hour 8 hours
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Pricing Consumption:
Compute = $0.12 / small instance hour Storage = $0.15 / GB stored / month Storage transactions = $0.01 / 10K Data transfers = $0.10 in / $0.15 out / GB - ($0.30
in / $0.45 out / GB in Asia) Reserved(Development Accelerator Core):
750 hours (small compute instance) 10 GBs of storage 1,000,000 storage transactions 7 GB in / 14 GB out(2.5 GB in / 5 GB out in Asia) For 6 month = $59.95 (42% off from consumption)
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Pricing Web Edition: Up to 1 GB relational database =
$9.99 / month Business Edition: Up to 10 GB relational
database = $99.99 / month Data transfers = $0.10 in / $0.15 out / GB -
($0.30 in / $0.45 out / GB in Asia)
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Possible Strategies Cost-based pricing
Flat pricing Tiered-pricing Performance-based pricing User-based pricing Usage-based pricing
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Possible StrategiesAmazon EC2
Google App Engine
Windows Azure
Low-price leader O O O
Experience-curve pricing ?
Bundling O O
Price signaling
Reference pricing ?
Image/prestige pricing O O O
Cost-plus pricing
Complementary pricing
Premium pricing
Random discounting ?
Periodic discounting ?
Second-market discounting *
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Possible Strategies Other effects
Similar prices (competing situation?)
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Conclusion&Comments In this paper, we have proposed architecture
for market-oriented allocation of resources within Clouds.
We have discussed some representative platforms for Cloud computing covering the state-of-the-art.
Comments: This paper has a simple but clear architecture
that we can use. (need add something detail) Some of the information of the cloud platform are
out of date, but the comparison is good.
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