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
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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
Introduction:definition
Definition of cloud:
 A Cloud is a type of parallel and distributed system;
 Consisting of a collection of interconnected and
virtualized computers
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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.”
Introduction:trend
Web Search Trends:
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[C]. Google and Salesforce.com in Cloud computing deal, Siliconrepublic.com - Apr 14 2008
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Market-Oriented Cloud Architecture
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Cloud providers will need to consider and meet different
QoS parameters of each individual consumer as
negotiated in specific SLAs.
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Traditional system-centric resource management
architecture are no longer fit
5
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Do not provide incentives for them to share their
resources.
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Regard all service requests to be of equal importance.
Market-Oriented Cloud Architecture
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Market-Oriented Cloud Architecture
Service Request Examiner and Admission Control:
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Interprets the submitted request for QoS requirements before
determining whether to accept or reject the request.
Pricing:
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The Pricing mechanism decides how service requests are
charged.
 Ex. submission time (peak/off-peak)
, pricing rates (fixed/changing)
Accounting:
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Maintains the actual usage of resources by requests and
historical information usage.
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Final cost to charge users.
Improve resource allocation decisions.
Market-Oriented Cloud Architecture
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VM monitor:
 Keep track of the availability of VMs and their resource
entitlements.
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Dispatcher:
 starts the execution of accepted service requests
on allocated VMs.
 Service Request Monitor:
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keeps track of the execution progress of service
requests.
Qos parameter issue
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In cloud there are critical QoS parameters to consider in
a service request
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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].
9 [8]S.Venugopal, X. Chu, and R. Buyya. using the Alternate Offers Protocol (IWQoS 2008), A Negotiation Mechanism for Advance
Resource Reservation
Commercial offering of market-oriented
Clouds requirement

Customizable

Support customer-driven service management based on
customer profiles and requested service requirements.
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Market-based resource management
 Contain computational risk management to sustain SLAoriented resource allocation.
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Incorporate autonomic resource management models:
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Effectively self-manage changes in service requirements to
satisfy both new service demands and existing service
obligations.
Emerging cloud platform
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Amazon EC2
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Amazon EC2
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Instances Types (Memory / *ECU / Storage / Platform)
Standard Instances
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High-Memory Instances
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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
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
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Medium: 1.7 GB / 5 / 350 GB / 32-bit
Extra Large: 7 GB / 20 / 1690 GB / 64-bit
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http://aws.amazon.com/ec2/
About Measuring Compute Resources
(quote from Amazon)
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*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.”
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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.”
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pay by the hour
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
$1.24
Unit: Per Hour
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Reserved Instances
Linux/UNIX
One-time fee
US – N.
Virginia
US – 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
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Spot Instances enable you to bid for unused Amazon EC2 capacity.
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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
17 *fluctuates periodically depending on the supply of and demand for Spot Instance
Data Transfer
Internet 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
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Amazon Elastic Block Store
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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)
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Amazon CloudWatch is a web service that provides monitoring for
AWS cloud resources.
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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
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Elastic Load Balancing automatically distributes incoming application
traffic across multiple Amazon EC2 instances.
Charged per hour and GB of data processed
Google App Engine
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Google App Engine
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Run web applications on Google’s infrastructure
Programming language support: python, java
Pricing:
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Quota
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Fixed quota (for free)
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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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Mail
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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
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Windows Azure platform
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Provides a scalable environment with compute, storage, hosting,
and management capabilities.
SQL Azure
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A Relational Database for the Cloud(Windows Azure
platform).
Microsoft Windows Azure
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During Community Technology Preview (CTP), services
included in Windows Azure will be available without
charge
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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
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Jan 1, 2010
First month without charge
Pricing unit
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Compute Instances:
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(Instance Size, CPU, Memory, Storage, I/O Performance )
Small --------1.6 GHz ,1.75 GB, 225 GB, Moderate
Medium --2 x 1.6 GHz , 3.5 GB, 490 GB, High
Large----- 4 x 1.6 GHz, 7 GB, 1,000 GB, High
Extra large-8 x 1.6 GHz, 14 GB, 2,040 GB, High
Instance hour transformation:
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Instance Size
1 hour
Medium
Large
Extra large
Elapsed Hour Small Instance Hours Small
1 hour
1 hour
2 hours
1 hour
4 hours
1 hour
8 hours
Pricing
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Consumption:
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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):
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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)
Pricing
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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
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Cost-based pricing
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Flat pricing
Tiered-pricing
Performance-based pricing
User-based pricing
Usage-based pricing
Possible Strategies
Amazon
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
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Other effects
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Similar prices (competing situation?)
Conclusion&Comments
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In this paper, we have proposed architecture for marketoriented allocation of resources within Clouds.
We have discussed some representative platforms for
Cloud computing covering the state-of-the-art.
Comments:
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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.