1. Prof. Neeraj Bhargava
Pooja Dixit
Department of Computer Science
School of Engineering & System Sciences
MDS, University Ajmer, Rajasthan, India
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2. A lot of heterogeneous hardware is used in order to create the Grid and, in
addition, these devices are not managed by only one person but by different
system administrators in each of the companies. Grid follows the challenges that
need to be resolved to harness the full power of grid:-
No clear standard:-Grid computing uses various standards, but all grids are not
use same standards. Example all grid operating system such as Linux, Apache and
My SQL are using WSRF, UDDI, WWW, SOAP and XML standards. Oracle 10g
enterprise implement without WSRF. IBM develops the Grid middleware based on
J2EE. We cannot use different OS at the same machine in the same time in grid
computing.
Distributed computing Vs Grid computing: - Grid computing involves dynamic
virtual organisation, resource sharing and peer to peer computing. The Grid
intends to make access to computing power, scientific data repositories and
experimental facilities as easy as the Web makes access to information. Same all
facilities provide the grid computing. So it is a challenge for grid computing.
Lack of grid enabled software: - The software, which are enabled the grid
computing are less, It has limited software on Grid. Much software has not
copyright issues and source code of licence. It is need for more company
developing grid-enabled version, need more developers on grid development and
need to develop open source software.
Sharing Resources between Various Types of Services:- Grid used for sharing
resource from various sites and grid hosts. It handles a massive amount of data as
a grid platform. A lot of sites and multiple servers gathered there it is so complex
infrastructure. It provides difficulty for hardware resource sharing within virtual
organisation.
Difficult to develop: - Grid programming used java, XML, use web services WSDD,
WSDL, UDDI, WSRF, and GT3developing guidelines. It is a matter who developing
the grid Applications. Basically that is available for senior computer science
developers and enterprise developers.
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3. Limited Area & Applications:-Grid computing is used to solve
for large and complex problems. Its area is limited such as
scientists, developer, analysis and researchers. Grid
computing is used in Hollywood flickers, industrial research,
and biometric research and engineering research. Grid cannot
use for common problems by common persons.
Management and Administration: - Many institutes and
organizations used grid computing. It distributes the
resources on large geographically distributed environments
and accesses the heterogeneous devices and machines. So it
is a major challenge to manage the administration of the grid
computing.
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4. All the resource available in the grid environment are basically owned
and managed by multiple organization. For the efficient operation of
computational grid various factors must be considered such as
resources sharing, and load balancing etc. The primary challenges
that should be taken into account for grid system are as followed:
Administration & Security
Solution Development
Resource heterogeneity
Accounting infrastructure
Programming for application development
Resource Management
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5. Exploiting underutilized Resources: One of the basic uses of grid computing is to run an
existing application on a different machine. The machine on which the application is normally
run might be unusually busy due to a peak in activity. The job in question could be run on an
idle machine elsewhere on the grid.
Parallel CPU capacity The potential for massive parallel CPU capacity is one of the most
common visions and attractive features of a grid. In addition to pure scientific needs, such
computing power is driving a new evolution in industries such as the bio-medical field,
financial modeling, oil exploration, motion picture animation, and many others.
Virtual resources and virtual organizations for collaboration: Another capability enabled by
grid computing is to provide an environment for collaboration among a wider audience. In the
past, distributed computing promised this collaboration and achieved it to some extent.
Access to additional resources: As already stated, in addition to CPU and storage resources, a
grid can provide access to other resources as well. The additional resources can be provided
in additional numbers and/or capacity.
Resource balancing: grid federates a large number of resources contributed by individual
machines into a large single-system image. For applications that are grid-enabled, the grid
can offer a resource balancing effect by scheduling grid jobs on machines with low utilization.
Reliability: High-end conventional computing systems use expensive hardware to increase
reliability. They are built using chips with redundant circuits that vote on results, and contain
logic to achieve graceful recovery from an assortment of hardware failures.
Management: The goal to virtualized the resources on the grid and more uniformly handle
heterogeneous systems will create new opportunities to better manage a larger, more
distributed IT infrastructure. It will be easier to visualize capacity and utilization, making it
easier for IT departments to control expenditures for computing resources over a larger
organization
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