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1. CLOUD COMPUTING VS
GRID COMPUTING
PRESENTER : OMID SOHRABI
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2. MAIN ARTICLE2

3. INTRODUCTION3
“computation may someday be organized as a public utility”
John McCarthy
Computing pioneer
developed the Lisp programming language family

4. INTRODUCTION (CONTINUE)4
TeraGrid is an open scientific discovery infrastructure combining leadership class
resources at eleven partner sites to create an integrated, persistent computational
resource

5. DEFINITION OF CLOUD COMPUTING
 There is little consensus on how to define the Cloud
 A large-scale distributed computing paradigm that is driven by economies
of scale, in which a pool of abstracted, virtualized, dynamically-scalable,
managed computing power, storage, platforms, and services are delivered
on demand to external customers over the Internet.
Ian Foster
 Cloud computing is using the internet to access someone else's software
running on someone else's hardware in someone else's data center.
Lewis Cunningham
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6. DEFINITION OF CLOUD COMPUTING
 There is little consensus on how to define the Cloud
 A large-scale distributed computing paradigm that is driven by economies
of scale, in which a pool of abstracted, virtualized, dynamically-scalable,
managed computing power, storage, platforms, and services are delivered
on demand to external customers over the Internet.
Ian Foster
 Cloud computing is using the internet to access someone else's software
running on someone else's hardware in someone else's data center.
Lewis Cunningham
6

7. Clouds: key points of the definition
 Differences related to traditional distributed paradigms:
 Massively scalable
 Can be encapsulated as an abstract entity that delivers different levels
of service
 Driven by economies of scale
 Services can be dynamically configured (via virtualization or other
approaches) and delivered on demand
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8. Clouds: reasons for interest
 Rapid decrease in hw cost, increase in computing power and
storage capacity (multi-cores etc)
 Exponentially growing data size
 Widespread adoption of Services Computing and Web 2.0
apps
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9. Clouds: relation with other paradigms9
A Web 2.0 site may allow users to interact and collaborate with each other in a social media dialogue as
creators of user-generated content in a virtual community, in contrast to Web sites where people are
limited to the passive viewing of content. Examples of Web 2.0 include social networking sites, blogs,
wikis, folksonomies, video sharing sites, hosted services, Web applications

10. GRID COMPUTING
 Grid Computing enables resource sharing and coordinated
problem solving in virtual organizations(VO) where each VO
can consist of either physically distributed institutions or
logically related projects/groups.
 Builds a uniform computing environment from diverse
resources by defining standard network protocols and
providing middleware to mediate access to a wide range of
heterogeneous resources (egGlobusToolkit).
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11. GRID COMPUTING (continue)11

12. How technologists perceive the Cloud
 “The interesting thing about Cloud Computing is that we’ve redefined Cloud
Computing to include everything that we already do. . . . I don’t understand what
we would do differently in the light of Cloud Computing other than change the
wording of some of our ads.”
12
Larry Ellison (Oracle CEO)
Wall Street Journal, September 26, 2008

13. How technologists perceive the Cloud
 “A lot of people are jumping on the [cloud] bandwagon, but I have not heard two
people say the same thing about it. There are multiple definitions out there of “the
cloud.”
13
Andy Isherwood (HP VP of sales)
ZDnetNews, December 11, 2008

14. How technologists perceive the Cloud
 “It’s stupidity. It’s worse than stupidity: it’s a marketing hype campaign. Somebody
is saying this is inevitable —and whenever you hear somebody saying that, it’s very
likely to be a set of businesses campaigning to make it true.”
14
Richard Stallman (Advocator of Free Software)
The Guardian, September 29, 2008

15. Is Cloud a new name for Grids?
 YES: the vision is the same
reduce the cost of computing
increase reliability
increase flexibility (transitioning from self-operation to third
party)
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The answer is complicated…
IT reinvents itself every five years

16. Is Cloud a new name for Grids?
 NO: things are different than 10 years ago
New needs to analyze massive data, increased demand for
computing
Billions of dollars being spent by Amazon, Google,Microsoft to
create real commercial large-scale systems with hundreds of
thousands of computers – www.top500.org shows computers
with 100,000+ cores
Only need a credit card to get on-demand access to infinite
computers
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17. Is Cloud a new name for Grids?
 Nevertheless YES: same problems but different details
Problems are the same in clouds and grids
How to manage large facilities
How to discover, request, and use resources
How to implement and execute parallel Computations
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18. Clouds: side-by-side comparison with
Grids
 Business model
 Architecture
 Resource Management
 Programming model
 Application model
 Security model
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19. Cloud vs Grids - Business model
 Traditional: one-time payment for unlimited use of software
 Clouds: pay the provider on a consumption basis, computing
and storage (like electricity, gas etc)
 Grids: assigned a number of service units
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20. Cloud vs Grids - Architecture20
communication
and authentication
protocols
discovery, negotiation,
monitoring, accounting and
payment of sharing operations
on individual resources
interactions across
collections of
resources,
directory services

21. Cloud vs Grids - Architecture21
resources that
have been
abstracted/encapsulated
collection of specialized
tools, middleware and
services on top of the unified
resources to provide a
development and/or
deployment platform

22. Cloud vs Grids - Architecture
SPI Model
 Cloud Software as a Service (SaaS)
 Cloud Platform as a Service (PaaS)
 Cloud Infrastructure as a Service (IaaS)
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23. Cloud vs Grids - Architecture
SPI MODEL (IaaS)
 The capability provided to the consumer is to provision
processing, storage, networks, and other fundamental
computing resources.
 Consumer is able to deploy and run arbitrary software, which
can include operating systems and applications.
 The consumer does not manage or control the underlying
cloud infrastructure but has control over operating systems,
storage, deployed applications, and possibly limited control of
select networking components (e.g., host firewalls).
 Typical examples are Amazon EC2 Service and S3
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24. Cloud vs Grids - Architecture
SPI MODEL (IaaS)
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25. Cloud vs Grids - Architecture
SPI MODEL (PaaS)
 The capability provided to the consumer is to deploy onto the
cloud infrastructure consumer created or acquired
applications created using programming languages and tools
supported by the provider.
 The consumer does not manage or control the underlying
cloud infrastructure including network, servers, operating
systems, or storage, but has control over the deployed
applications and possibly application hosting environment
configurations.
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26. Cloud vs Grids - Architecture
SPI MODEL (SaaS)
 The capability provided to the consumer is to use the
provider’s applications running on a cloud infrastructure.
 delivers special purpose software that is remotely accessible.
E.g,: Google Maps, Live Mesh from Microsoft etc
 The consumer does not manage or control the underlying
cloud infrastructure including network, servers, operating
systems, storage, or even individual application capabilities,
with the possible exception of limited userspecific application
configuration settings.
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27. Cloud vs Grids – Resource Management
 Compute model
 Data model
 Virtualization
 Monitoring
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28. Cloud vs Grids – Resource Management
COMPUTE MODEL
 Grids: batch-scheduled (queueing systems)
 Clouds: resources shared by all users at the same time in
contrast to dedicated resources in queueing systems
 Maybe one of the major challenges in clouds: QoS!
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29. Cloud vs Grids – Resource Management
DATA MODEL
 Data locality: to achieve good scalability data must be
distributed over many computers
 Clouds: use map-reduce mechanism like in Google to
maintain data locality
 In Grids, data storage usually relies on a shared file systems
(e.g. NFS, GPFS, PVFS, Luster), where data locality cannot be
easily applied
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30. Cloud vs Grids – Resource Management
Virtualization
 Abstraction and encapsulation
 Clouds: rely heavily on virtualization
 Supports cost-effective use of cloud’s physical resources
 Grids: do not rely on virtualization as much as clouds.
due to policy and having each individual organization
maintain full control of their resources
 However, there are efforts in Grids to use virtualization as well,
such as Nimbus
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31. Cloud vs Grids – Resource Management
Monitoring
 Virtualization poses challenges to fine-grained control over
monitoring
 Service-oriented view means resources below service API are
not visible
 Monitoring may not be as important because of abstractions
 Grid trust model allows users via their identity delegation to
access and browse resources at different sites
 Resources not highly abstracted & virtualized
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32. Cloud vs Grids – Programming Model
CLOUD
 most use the map-reduce programming model.
Implementation: Hadoop that uses Pig as a declarative
programming language
GRID
 Complicated by issues like multiple administrative domains,
resource heterogeneity, etc
 heavy use of workflow tools to be able to manage large sets
of tasks and data. others: MPICH-G2, WSRF, GridRPC…
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33. Cloud vs Grids – Application Model
CLOUD
 Traditionally can support same apps as grid except HPC (due
to low latency needs) but this is changing
 Interactive, loosely-coupled, transaction-oriented apps
GRID
 Batch-oriented apps
 Support High-Performance Computing (HPC) through High
Throughput Computing (HTC)
 Support workflows of loosely-coupled applications
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34. Cloud vs Grids – Security Model
 Clouds currently more homogeneous and single provider so
security simpler
 Still an important concern for cloud users
 Email address & credit card gets you an account
 Grids Built on assumptions of heterogeneous and dynamic resources
and multiple admin domains
 Stricter procedure to acquire an account
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35. CONCLUSION35

36. CONCLUSION (continue)36

37. REFRENCES
 Geelan, Jeremy. "Twenty-one experts define cloud computing." Cloud Computing
Journal 4 (2009): 1-5
 Foster, Ian, et al. "Cloud computing and grid computing 360-degree compared."
Grid Computing Environments Workshop, 2008. GCE'08. Ieee, 2008.
 Sharma, Prabha. "Grid Computing Vs. Cloud Computing." International Journal of
Information and Computation Technology. 2013 ISSN: 0974-2239
 Lewis Cunningham, Cloud Computing with Amazon and Oracle, 2008.
 www.teragrid.org
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38. THANKS FOR YOUR
ATTENTION
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