Utility Survey Wokingham Computing
Some think about this to function as "the third information technology wave" after the Internet and Web, and will be the backbone of another generation of services and applications that will further the study and development of GIS and related areas.
Grid computing allows for the sharing of processing power, enabling the attainment of high performances in computing, management and services. Grid computing, (unlike the traditional supercomputer that does parallel computing by linking multiple processors over something bus) uses a network of computers to execute a program. The problem of using multiple computers is based on the difficulty of dividing up the tasks among the computers, without having to reference portions of the code being executed on other CPUs.
Parallel processing
Parallel processing may be the usage of multiple CPU's to execute different sections of an application together. Remote sensing and surveying equipment have been providing vast levels of spatial information, and how to manage, process or dispose of this data have grown to be major issues in neuro-scientific Geographic Information Science (GIS).
To resolve these problems there's been much research into the section of parallel processing of GIS information. This calls for the utilization of a single computer with multiple processors or multiple computers which are connected over a network focusing on the same task. There are various types of distributed computing, two of the most common are clustering and grid processing.
The primary reasons for using parallel computing are:
Saves time.
Solve larger problems.
Provide concurrency (do multiple things concurrently).
Taking advantage of non-local resources - using available computing resources on a broad area network, and even the Internet when local computing resources are scarce.
Cost savings - using multiple cheap computing resources rather than paying for time on a supercomputer.
Overcoming memory constraints - single computers have very finite memory resources. For large problems, utilizing the memories of multiple computers may overcome this obstacle.
Limits to serial computing - both physical and practical reasons pose significant constraints to simply building ever faster serial computers.
Limits to miniaturization - processor technology is allowing a growing amount of transistors to be placed on a chip.
However, despite having molecular or atomic-level components, a limit will be reached on what small components could be.
Economic limitations - it really is increasingly expensive to make a single processor faster. Using a larger number of moderately fast commodity processors to achieve the same (or better) performance is less expensive.
The future: during the past a decade, the trends indicated by ever faster networks, distributed systems, and multi-processor computer architectures (even at the desktop level) clearly show that parallelism may be the future of computing.
Distributed GIS
As the development of GIS sciences and technologies go further, increasingly level of geospatial and non-spatial data get excited about GISs due to more diverse data sources and development of data collection technologies. GIS data are generally geographically and logically distributed and GIS functions and services do. Spatial analysis and Geocomputation are getting more complex and computationally intensive. Sharing and collaboration among geographically dispersed users with various disciplines with various purposes are receiving more necessary and common. A dynamic collaborative model " Middleware" is necessary for GIS application.
Computational Grid is introduced as a possible solution for the next generation of GIS. Basically, the Grid computing concept is supposed to enable coordinate resource sharing and problem solving in dynamic, multi-organizational virtual organizations by linking computing resources with high-performance networks. Grid computing technology represents a new method of collaborative computing and problem solving in data intensive and computationally intensive environment and has the opportunity to satisfy all the requirements of a distributed, high-performance and collaborative GIS. Some methodologies and Grid computing technologies as solutions of requirements and challenges are introduced make it possible for this distributed, parallel, and high-throughput, collaborative GIS application.
Security
Security issues in that wide area distributed GIS is critical, which include authentication and authorization using community policies as well as allowing local control of resource. Grid Security Infrastructure (GSI), combined with GridFTP protocol, makes certain that sharing and transfer of geospatial data and Geoprocessing are secure in the Computational Grid environment.
Conclusion
Because the conclusion, Grid computing has the possiblity to lead GIS right into a new "Grid-enabled GIS" age with regard to computing paradigm, resource sharing pattern and online collaboration.