Grid Computing In Distributed GIS

Grid Computingprocessors to achieve the same (or better)
Some consider this to be the "the thirdperformance is less expensive.
information technology wave" after the InternetThe future: during the past 10 years, the trends
and Web, and will be the backbone of the nextindicated by ever faster networks, distributed
generation of services and applications that aresystems, and multi-processor computer
going to further the research and development ofarchitectures (even at the desktop level) clearly
GIS and related areas.show that parallelism is the future of computing.
Distributed GIS
Parallel processingAs the development of GIS sciences and
Parallel processing is the use of multiple CPU's totechnologies go further, increasingly amount of
execute different sections of a program together.geospatial and non-spatial data are involved in
Remote sensing and surveying equipment haveGISs due to more diverse data sources and
been providing vast amounts of spatialdevelopment of data collection technologies. GIS
information, and how to manage, process ordata tend to be geographically and logically
dispose of this data have become major issues indistributed as well as GIS functions and services
the field of Geographic Information Science (GIS).do. Spatial analysis and Geocomputation are
To solve these problems there has been muchgetting more complex and computationally
research into the area of parallel processing ofintensive. Sharing and collaboration among
GIS information. This involves the utilization of ageographically dispersed users with various
single computer with multiple processors ordisciplines with various purposes are getting more
multiple computers that are connected over anecessary and common. A dynamic collaborative
network working on the same task. There aremodel " Middleware" is required for GIS application.
many different types of distributed computing,Computational Grid is introduced as a possible
two of the most common are clustering and gridsolution for the next generation of GIS. Basically,
processing.the Grid computing concept is intended to enable
The primary reasons for using parallel computingcoordinate resource sharing and problem solving in
are:dynamic, multi-organizational virtual organizations
Saves time.by linking computing resources with
Solve larger problems.high-performance networks. Grid computing
Provide concurrency (do multiple things at thetechnology represents a new approach to
same time).collaborative computing and problem solving in
Taking advantage of non-local resources - usingdata intensive and computationally intensive
available computing resources on a wide areaenvironment and has the chance to satisfy all the
network, or even the Internet when localrequirements of a distributed, high-performance
computing resources are scarce.and collaborative GIS. Some methodologies and
Cost savings - using multiple cheap computingGrid computing technologies as solutions of
resources instead of paying for time on arequirements and challenges are introduced to
supercomputer.enable this distributed, parallel, and high-throughput,
Overcoming memory constraints - singlecollaborative GIS application.
computers have very finite memory resources.Security
For large problems, using the memories of multipleSecurity issues in such a wide area distributed GIS
computers may overcome this obstacle.is critical, which includes authentication and
Limits to serial computing - both physical andauthorization using community policies as well as
practical reasons pose significant constraints toallowing local control of resource. Grid Security
simply building ever faster serial computers.Infrastructure (GSI), combined with GridFTP
Limits to miniaturization - processor technology isprotocol, makes sure that sharing and transfer of
allowing an increasing number of transistors to begeospatial data and Geoprocessing are secure in
placed on a chip.the Computational Grid environment.
However, even with molecular or atomic-levelConclusion
components, a limit will be reached on how smallAs the conclusion, Grid computing has the chance
components can be.to lead GIS into a new "Grid-enabled GIS" age in
Economic limitations - it is increasingly expensiveterms of computing paradigm, resource sharing
to make a single processor faster. Using a largerpattern and online collaboration.
number of moderately fast commodity