Grid computing is a distributed computing approach that allows users to access networked computer systems and resources located across different areas. It provides computing resources like processors, storage, and applications to users regardless of where those resources are located, similar to how the electrical power grid provides electricity to users without knowledge of its source. Key benefits of grid computing include solving large-scale problems through parallel processing and optimally utilizing idle computing resources. Security, licensing, and performance monitoring present challenges to grid computing's adoption.

1. GRID
COMPUTING
S U B M I T T E D T O : S U B M I T T E D B Y :
D R . M A N A V J E E T K A U R D E E P A N S H U
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2. WHAT IS GRID COMPUTING?
Grid computing is a distributed
computing approach where the end user will
be ubiquitously offered any of the services of a
“grid” or a network of computer systems
located either in a Local Area Network (LAN) or
in a Wide Area Network (WAN) in a spread of
geographical area.

3. ANALOGY WITH ELECTRICAL POWER
GRID
• Electrical power
grid
• users (or electrical
appliances) get access to
electricity through wall
sockets with no care or
consideration for where or
how the electricity is
actually generated.
• “The power grid” links
together power plants of
many different kinds
• The Grid
• users (or client applications) gain access
to computing resources (processors,
storage, data, applications, and so on)
as needed with little or no knowledge
of where
those resources are located or what the
underlying technologies, hardware,
operating system, and so on are.
• "the Grid" links together computing
resources (PCs, workstations, servers,
storage elements) and provides the
mechanism needed to access them.

4. DISTRIBUTED COMPUTING VS GRID
• Grid is an evolution of distributed computing
– Dynamic
– Geographically independent
– Built around standards
– Internet backbone
• Distributed computing is an ―older term
– Typically built around registered software and network
– Tightly couples systems/organization

5. WHO NEEDS GRID COMPUTING?
• Not just computer scientists…
• scientists “hit the wall” when faced with situations:
• The amount of data they need is huge and the data is stored in different institutions.
• The amount of similar calculations the scientist has to do is huge.
• Other areas:
– Government
– Business
– Education
– Industrial design ….
• Academic
– Big science
– Life science
– Nuclear engineering
– Simulation…
• Storage density
doubles every 12
months
• Dramatic growth in
online data (1
petabyte =1000
terabyte = 1,000,000
gigabyte)

6. GRID TOPOLOGIES
• Intragrid
– Local grid within an organization
– Trust based on personal contracts
• Extragrid
– Resources of a consortium of organizations connected through a (Virtual) Private
Network
– Trust based on Business to Business contracts
• Intergrid
– Global sharing of resources through the internet
– Trust based on certification

9. MIDDLEWARES USED..
• Globus –chicago Univ
• Condor – Wisconsin Univ – High throughput computing
• Legion – Virginia Univ – virtual workspacescollaborative computing
• IBP – Internet back pane – Tennesse Univ – logistical networking
• NetSolve – solving scientific problems in heterogeneous env. – high throughput &
data intensive

10. GRID IN INDIA -GARUDA
GARUDA is India's Grid Computing initiative connecting 17 cities across the
country.
•The 45 participating institutes in this nationwide project include all the IITs and C-
DAC centers and other major institutes in India.

12. LASER INTERFEROMETER GRAVITATIONAL
WAVE OBSERVATORY (LIGO)
• Instruments at two sites to detect gravitational waves
• Each experiment run produces millions of files
• Scientists at other sites want these datasets on local storage
• LIGO deploys RLS servers at each site to register local mappings and collect info about
mappings at other sites
LARGE SCALE DATA REPLICATION FOR LIGO
Goal: detection of gravitational waves
– Generate 1 TB of data daily
– Need to replicate this data across 9 sites to make it available to scientists
– Scientists need to learn where data items are, and how to access them
As of December 2018, LIGO
has made eleven detections of
gravitational waves, of which
ten are from binary black
hole mergers. The other
event was the first detection of
a collision of two neutron
stars, on 17 August 2017 which
simultaneously produced
optical signals detectable by
conventional telescopes.

13. HOW SATELLITE’s SEVERAL IMAGES RENDERS INTO A
READABLE IMAGE? (NASA)

14. RENDERING OF RAW IMAGE DONE
WITH GRID COMPUTING
FOR EX. WEATHER FORCAST, GIS,
GOOGLE MAPS

17. XML AND HTML
Correct Answer :
XML is used for exchanging data, HTML is not.
XML stands for "Extensible Markup Language". It is some
what like HTML but its is used to describe data not to
display data.
XML was designed to describe data, with focus on what
data is.
HTML is "Hyper Text Markup Language". HTML was
designed to display data, with focus on how data looks.
XML Database is used to store huge
amount of information in the XML format.
As the use of XML is increasing in every
field, it is required to have a secured
place to store the XML documents. The
data stored in the database can be
queried using XQuery, serialized, and
exported into a desired format.

18. BENEFITS OF GRID COMPUTING
• Grid computing solve Challenging problems such as earthquake simulation and
weather modeling. Grids computing is a way of using resources optimally inside an
organization.
• Grid architecture can also be used for load balancing and redundant network
connections. This Model use parallel processing software that divide a program among
the many thousand computers and Collect and combine the results into a single solution.
For the security reasons, grid computing is restricted within the same organization.
• Grid computing can be used in a large Networks where thousands of machines sit idle at
any given moment. Even when a user is reading, it constitutes idle time. These idle power
of computers can be used for large computational problems, these technique is running
in the background that is known as cycle-scavenging.

19. DISADVANTAGES OF GRID COMPUTING
• Licensing across many servers may
make it prohibitive for some apps.
• Vendors are starting to be more
flexible with environment like this.
• Security
Confidentiality, Integrity, Access to
resources, data.
• Performance monitoring
Zoning mechanisms to ensure
applications competing for resources
do not affect each other

21. REFERENCES
• http://www.jatit.org/distributed-computing/grid-vs-distributed.htm
• https://en.wikipedia.org/wiki/LIGO
• http://www.it.uom.gr/teaching/unc_charlottePPG/grid.htm
• https://www.youtube.com/watch?v=esVzoSqQ1Pc
• SATELLITE IMAGE PROCESSING ON A GRID BASED COMPUTING ENVIRONMENT
https://ijcsmc.com/docs/papers/March2014/V3I3201446.pdf

22. THANK YOU