17 Manjula Shanbhog Research Letter Aug 2011

7/30/2019 17 Manjula Shanbhog Research Letter Aug 2011

http://slidepdf.com/reader/full/17-manjula-shanbhog-research-letter-aug-2011 1/5

Available ONLINE www.visualsoftindia.com/journal.html

VSRD-IJCSIT, Vol. 1 (6), 2011, 460-464

____________________________

1Lecturer, Department of Computer Science, Hierank Business School, Noida, Uttar Pradesh, INDIA.*Correspondence : [email protected]

R R R EEE SSS EEE AAA R R R CCC HHH LLL EEE TTT TTT EEE R R R

Grid and Scalable Computing1

Manjula Shanbhog*

ABSTRACT

Grid computing is more than just communicating between computers: it is a way to share computing power. It is

basically a form of networking .Unlike conventional networks that focus on communication among devices, grid

computing harnesses unused processing cycles of all computers in a network involving huge amounts of data

and for solving problems too intensive for any stand-alone machine. It allows us to unite pools of servers,

storage systems and networks into a single large system so we can deliver the power of multiple-systems

resources to a single user point for a specific purpose. To a user, data file, or an application, the system appears

to be a single, enormous virtual computing system.

Grid computing is the next logical step in distributed networking. Just as the Internet allows users to share ideas

and files as the seeds of projects, grid computing lets us share the resources of disparate computer systems. The

major purpose of a grid is to visualize resources to solve problems. So, rather than using a network of computers

simply to communicate and transfer data, The grid computing helps in exploiting underutilized resources,

achieving parallel CPU capacity; provide virtual resources for collaboration and reliability.

This new approach is known by several names, such as Meta computing, scalable computing, global computing,

Internet computing and more recently peer-to-peer or Grid computing.

Keywords : Grid Computing; Processing Cycles; Pools of Server; Disparate Computer Systems; Underutilized

Resources; Virtual Resources.

1. INTRODUCTION

As a result of the invention of technically faster hardware and more sophisticated software, in the recent years

we have seen a substantial increase in the network performance. Nevertheless, there are still problems, in the

fields of science, engineering, and business, which cannot be effectively dealt with using the current generation

of supercomputers. In fact, due to their size and complexity, these problems are often very numerically and/or



Manjula Shanbhog et. al / VSRD International Journal of CS & IT Vol. 1 (6), 2011

Page 461 of 464

data intensive and consequently require a variety of heterogeneous resources that are not available on a single

machine. Grid computing is used for those problems that are beyond the processing limits of individual

computers. Right now the primarily use of such computing is in the field of scientific or technical projects such

as cancer and other medical research -- projects that involve the analysis of inordinate amounts of data.

2. THE BASICS

Grid computing joins together many individual computers, creating a large system with massive computational

power that far surpasses the power of a handful of supercomputers. Because the work is split into small pieces

that can be processed simultaneously, research time is reduced from years to months. The technology is also

more cost-effective, enabling better use of critical funds

3. HOW IT WORKS

In the global grid computing scenario, unused processing power on local clusters of computers scattered across

the Internet would be harnessed to address a single, complex application. Grid computing works by distributing

computational resources but maintaining central control of the process. A central server acts as a team leader

and traffic monitor.

This controlling cluster server divides a task into subtasks, and then assigns the work to computers with surplus

processing power on the grid. It also monitors the processing and, if the subtask routine fails, it will restart or

reassign it. When all the subtasks have been completed, the controlling cluster server aggregates the results and

advances to the next task until the whole job is completed. In a grid campus, a hierarchical structure of many

grid servers may handle subtasks, but all processing occurs on a single network.

In a global grid, machines can be on many different networks and on the Web. Because they're processing in so

many different circumstances, network latency can be a problem. But before any processing can occur, available

resources must be identified and located. Access to them must be negotiated, and the hardware and software

must be configured to effectively use the resources, which often are many smaller computers.

Fig: Working of Grid Computing




Page 462 of 464

4. SOME EXAMPLES OF CURRENT USES OF GRID COMPUTING

Perhaps the most ambitious is Oxford University's Centre for Computational Drug Discovery's project that

utilizes more than one million PCs to look for a cancer cure. People around the world donate a few CPU cycles

from their PCs through "screensaver time." The project eventually will analyze 3.5 billion molecules for cancer-

fighting potential. More than 50,000 years of CPU power (based on a 1.5 gigahertz chip) have been put to work

so far.

One highly publicized project is the SETI (Search for Extraterrestrial Intelligence) @Home project, in which PC

users worldwide donate unused processor cycles to help the search for signs of extraterrestrial life by analyzing

signals coming from outer space

5. THE FIVE BIG IDEAS BEHIND GRID COMPUTING

Resource sharing on a global scale: Sharing is the very essence of grid computing.

Secure access: There must be a high level of trust between resource providers and users, who often don't

know each other. Sharing resources is fundamentally in conflict with the conservative security policies

being applied at individual computer centers and on individual PCs. So getting grid security right is crucial.

Resource use : Demand for grid resources should be balanced, so that computers everywhere are used

more efficiently.

The death of distance: For grids to work, we need to ensure that distance makes no difference to efficient

access to computer resources.

Open standards : Open standards are needed to ensure that grids are interoperable and that everyone can

contribute constructively to grid development. Standardization also encourages industry to invest in

developing commercial grid services and infrastructure

6. CONCERNS ABOUT GRID COMPUTING

Whenever you link two or more computers together, you have to prepare yourself for certain questions. How do

you keep personal information private? How do you protect the system from malicious hackers? How do you

control who can access the system and use its resources? How do you make sure the user doesn't tie up all the

system resource?

The short answer to this question is middleware. There's nothing inherent in a grid computing system that can

answer these questions. The emerging protocols for grid computing systems are designed to make it easier for

developers to create applications and to facilitate communication between computers.

The most prevalent technique computer engineers use to protect data is encryption. To encrypt data is to encode

it so that only someone possessing the appropriate key can decode the data and access it. Ironically, a hacker

could conceivably create a grid computing system for the purpose of cracking encrypted information. Becauseencryption techniques use complicated to encode data, it would take a normal computer several years to crack a




Page 463 of 464

code (which usually involves finding the two largest prime divisors of an incredibly large number). With a

powerful enough grid computing system, a hacker might find a way to reduce the time it takes to decipher

encrypted data.

It's hard to protect a system from hackers, particularly if the system relies on open standards. Every computer in

a grid computing system has to have specific software to be able to connect and interact with the system as a

whole -- computers don't know how to do it on their own. If the computer systems software is proprietary, it

might be harder (but not impossible) for a hacker to access the system.

In most grid computing systems, only certain users are authorized to access the full capabilities of the network.

Otherwise, the control node would be flooded with processing requests and nothing would happen (a situation

called deadlock in the IT business). It's also important to limit access for security purposes. For that reason,

most systems have authorization and authentication protocols. These protocols limit network access to a select

number of users. Other users are still able to access their own machines, but they can't leverage the entire

network.

The middleware and control node of a grid computing system are responsible for keeping the system running

smoothly. Together, they control how much access each computer has to the network's resources and vice versa.

While it's important not to let any one computer dominate the network, it's just as important not to let network

applications take up all the resources of any one computer. If the system robs users of computing resources, it's

not an efficient system.

7. CONCLUSION

Grid computers stand to be the new era of computers. Grid computing made solving tasks of computers play

easy. It’s like "With a million people you can create a road in one day, one worker needs a million days to do the

same."

8. FUTURE SCOPE

Grid computing gain more importance in the near future because the number of applications exploiting large

scale data resources will continue to increase . Further, the smart combination of online data from sensor

networks and arbitrary archives on the one hand and computing facilities on the other hand will provide novel

services that do not only benefit scientific fields, like particle physics or climate research, but also reach into

industrial and societal domains.

9. REFERENCES[1] Fundamentals of Grid Computing – IBM Redbooks www.redbooks.ibm.com/redpapers/pdfs/redp3613.pdf

[2] Fran Berman, Geoffrey Fox, Anthony J. G. Hey, “Grid computing: making the global infrastructure a

reality”

[3] The Grid Computing Information Centre (GRID Infoware: http://www.gridcomputing.com

[4] http://www.gridcomputing.com/

[5] Introduction to Grid Computing: www.isi.edu/~annc/classes/grid/lectures/lecture1.pdf




Page 464 of 464

[6] Foster, I and Kesselman C, The Grid: blueprint for a future computing infrasture, Morgan Kauffmann

publishers, USA, 1999

[7] E.Cody, R.Sharman, “Security in grid computing: A review and synthesis,” Decision support system

volume 44,pp.749-769, March 2008

[8] M. Smith, M.Schmidt, “Secure on-demand grid computing,” Future Generation Computer systems, vol.25,

pp.135-325, March 2009.

Documents

17 Manjula Shanbhog Research Letter Aug 2011