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Cloud Computing and Grid Computing 360-Degree Compared

PRESENTED BY

MD. HASIBUR RASHID

By Ian Foster, Yong Zhao, Ioan Raicu, Shiyong Lu

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Introduction

Cloud Computing has become another buzzword after Web 2.0. On Cloud Computing is not a completely new concept; it has intricate connection to the relatively new but thirteen-year established Grid Computing paradigm, and other relevant technologies such as utility computing, cluster computing, and distributed systems in general.

This paper strives to compare and contrast Cloud Computing with Grid Computing from various angles and give insights into the essential characteristics of both.

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Cluster Computing

A cluster is a collection of parallel or distributed computers which are interconnected among themselves using high-speed networks, such as gigabit Ethernet, SCI, Myrinet and Infiniband.

Clusters are used mainly for high availability, load-balancing and for compute purpose.

When multiple computers are linked together in a cluster, they share computational workload as a single virtual computer.

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Grid Computing

Grid computing combines computers from multiple administrative domains to reach a common goal, to solve a single task, and may then disappear just as quickly.

Grid as a type of parallel and distributed system that enables the sharing, selection, and aggregation of geographically distributed autonomous resources dynamically at runtime depending on their availability, capability, performance, cost, and users quality-of-service requirements.

Grid computing is extended of Cluster computing.

• PC1• PC2• PC100

• PC1• PC2• PC50

• PC1• PC2• PC300

• PC1• PC2• PC20

CLUSTER1

CLUSTER2

CLUSTER4

CLUSTER3

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Cloud Computing

Cloud computing refers to both the applications delivered as services over the Internet and the hardware and system software in the data centers that provide those services.

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 agreement.

Extend of Grid Computing.

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Services of Cloud

Cloud computing provides basically three kinds of service:

SaaS: Software as a Service. Example service providers are Salesforce, Customer Relationships Management(CRM) system and Google Apps, MS Office Online.

PaaS: Platform as a Service. Some example service providers are Google’s App Engine , Microsoft Azure , RightScale and SalesForce .

IaaS: Infrastructure as a Service. Some of the IaaS providers are AWS, Eucalyptus, Open Stack, GoGrid and Flexiscale.

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Services of Cloud

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Challenges in the cloud computing

Dynamic scalability

Multi-tenancy

Querying and access

Standardization

Reliability and fault-tolerance

Debugging and profiling

Security and privacy

Power

9COMPARISON OF CLUSTER, GRID AND CLOUDCOMPUTING

Cluster Grid Cloud

Resource Handling Centralized Distributed Both

Loose coupling / Scalable No Both Yes

Reliability/ User friendliness

No Half Full

Network type Private Private Public Internet

Virtualization Half Half Yes

Business Model No No Yes

Task Size Single large Single large Small, medium & large

Heterogeneity No Yes Yes

Security High Medium / High Low / Medium

Value Added Service No Both Yes

Cost Very High High Low

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Architectural Comparison

11Cluster computing projects and applications

Condor : Research, Engineering of complex software, Maintenance of production environments, Education of students.

The Weather Research and Forecast (WRF), Hadoop Project.

Clusters were also used for solving grand challenging applications such as weather modeling, automobile crash simulations, life sciences, computational fluid dynamics, nuclear simulations, image processing, electromagnetic, data mining, aerodynamics and astrophysics.

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Grid Projects and applications

Globus, EGI-InSPIRE, NSFs National Technology Grid, NASAs Information Power Grid , GriPhyN, NEESgrid, Particle Physics Data Grid and the European Data Grid

The grid applications range from advanced manufacturing, numerical wind tunnel, oil reservoir simulation, particle physics research, High Energy Nuclear Physics (HENP), weather modeling, bio-informatics, terrain analysis of nature observation, scientific database, and popular science web services.

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Cloud Projects and Applications

CERN, Unified Cloud Interface (UCI), Cloud-Enabled Space Weather Platform (CESWP), OpenNebula, RoboEarth, Panda Cloud antivirus, Cloudo.

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Conclusion

We have presented a detailed comparison on the three computing models, cluster, grid and cloud computing Grid and cloud computing appears to be a promising model especially focusing on standardizing APIs, security, interoperability, new business models, and dynamic pricing systems for complex services. Hence there is a scope for further research in these areas.

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Thank You

Md. Hasibur Rashid, MSc. In CSE, KUET, Bangladesh.