Grid computing allows for the sharing of computer resources across a network. It utilizes both reliable tightly-coupled cluster resources as well as loosely-coupled unreliable machines. The grid system balances resource usage to provide quality of service to participants. Grid computing works by having at least one administrative computer and middleware that allows computers on the network to share processing power and data storage. It has advantages like improved efficiency, resilience, and ability to handle large-scale applications, but also challenges around resource sharing and licensing across multiple servers.

1. GRID COMPUTING
PRESENTED BY : Richa Chaudhary

2. AGENDA
What is Grid Computing ?
 How Grid Computing Works ?
 Reasons for using Grid
Computing ?
 Grid Architecture
 Grid computing behavior
 Advantages and Disadvantages

3. WHAT IS A GRID ?
Grid is a shared collection of reliable
(cluster-tightly coupled) &
unreliable resources (loosely
coupled machines) and interactively
communicating researchers of
different virtual organisations
(doctors, biologists, physicists).
Grid System controls and
coordinates the integrity of the Grid
by balancing the usage of reliable
and unreliable resources among its
participants providing better quality
of service.

4. Grid computing is a method of harnessing the power of many computers in a
network to solve problems requiring a large number of processing cycles and
involving huge amounts of data. Most organizations today deploy firewalls around
their computer networks to protect their sensitive proprietary data. But the central
idea of grid computing-to enable resource sharing makes mechanisms such as
firewalls difficult to use

5. How Grid computing works ?
In general, a grid computing
system requires:
 At least one computer,
usually a server, which
handles all the
administrative duties for
the System
 A network of computers
running special grid
computing network
software.
 A collection of computer
software called
middleware

6. Grid Architecture

7. Working of layers
 Fabric. The lowest layer job is used to make a common interface on all
possible kinds of resources available. Access by higher layers is granted via
standardized processes.
 Resource and connectivity protocols: The connectivity layer defines the
basic communication- and authentication protocols which are needed by the
grid. While the communication protocols allow the exchange of files
between different resources connected by the first layer, the authentication
protocols allow to communicate confidentially and to ensure the identity of
the two partners.
 Collective services: The purpose of this layer is the coordination of multiple
resources. Access to these resources doesn’t happen directly but merely via
the underlying protocols and interfaces.
 User applications: To this layer belong all those applications which are
operating in the environment of a virtual organization. Jobs of the lower
layers get called by applications and can use resources transparently.

8. Difference between grid &
distributed computing

9. Advantages of Grid Computing
Business benefits Technology benefits
 Improve efficiency by  Federate data and distribute it globally.
improving computational Support large multi-disciplinary
capabilities collaboration across organizations and
 Bring together not only IT business.
resources but also people.  Enable recovery and failure
 Create flexible, resilient  Ability to run large-scale applications
operational infrastructures comprising thousands of computes, for
 Address rapid fluctuations in wide range of applications.
customer demands.  Reduces signal latency – the delay that
builds up as data are transmitted over
the Internet.

10. Disadvantages of Grid Computing
 Resource sharing is further complicated when grid is introduced
as a solution for utility computing where commercial applications
and resources become available as shareable and on demand
resources.
 The concept of commercial on-demand shareable adds new, more
difficult challenges to the already complicated grid problem list
including service level features, accounting, usage metering,
flexible pricing, federated security, scalability, and open-ended
integration.
 Some applications may need to be tweaked to take full advantage
of the new model.
 Licensing across many servers may make it prohibitive for some
apps. Vendors are starting to be more flexible with environment
like this.

11. Applications
• Distributed supercomputing
• High-throughput computing
• On-demand computing
• Data-intensive computing
• Collaborative computing

12. THANK YOU !!