Grid Computing and its Application to Geoinformatics

Grid Computing and its Application to Geoinformatics

Aijun Chen (George Mason University, USA), Liping Di (George Mason University, USA), Yuqi Bai (George Mason University, USA) and Yaxing Wei (George Mason University, USA)
Copyright: © 2009 |Pages: 9
DOI: 10.4018/978-1-59140-995-3.ch027
OnDemand PDF Download:
No Current Special Offers


The definition of the Grid computing and its application to geoinformatics are introduced. Not only the comparison of power Grid and computing Grid is illustrated, also Web technology and Grid technology are compared. The Hourglass Model of Grid architecture is depicted. The layered Grid architecture, relating to Internet protocol architecture, consists of the fabric (computer, storage, switches, etc.) layer, connectivity layer, resource layer, collective layer, and application layer. Grid computing has been applied to many disciplines and research areas, such as physics, Earth science, astronomy, bioinformatics, etc. By applying the Grid computing to Open Geospatial Consortium, Inc.’s Web services and geospatial standards from International Organization for Standardization, US Federal Geographic Data Committee and US NASA, a geospatial Grid is proposed here, which consisting of Grid-managed geospatial data and Grid-enabled geospatial services.
Chapter Preview


Grid computing is not simply a means for researchers to do existing research faster, but also promises them a number of new capabilities. While the ability to carry out existing experiments in less time is definitely beneficial, other features such as ease of collaboration, reduced cost, and access to increased resources and instrumental results, allow more advanced research to be carried out. In order to achieve these goals, considerable work has been put into Grid-enabling technology, including Grid architecture, Grid middleware, authentication mechanisms, resource schedulers, data management and information services. These technologies form the basic services for achieving the goals of the Grid – creating e-Research and e-Commercial environments (Hey & Trefethen 2002).

The ultimate target of Grid Computing is to establish the Computational Grid whose idea is analogous to the electric power grid where power generators are distributed, but the users are able to access electric power without concern for the source of energy and its location (Figure 1). Today, the Grid computing technology is trying to provide computing capabilities as the electric power grid provides energy capabilities by using the same characteristics such as reliability, scalability, security, low cost, and convenience.

Figure 1.

Computational power grid analogous to electric power grid (Myrseth, 2002)


Grid technology has boomed as a result of the Internet and the rapid development of Web technology. As the Web revolutionizes information sharing by providing a universal protocol and syntax (HTTP and HTML) for information exchange, The Grid, which mainly consists of the standard protocols and syntaxes, comes up for revolutionizing general resource sharing. The similarity between Web and Grid technology is illustrated in Figure 2. (WS-* means that Web Service Resources Framework (WSRF)-related specifications about Web Services)

Figure 2.

Comparison of Web technology with Grid technology


Key Terms in this Chapter

Virtual Organization (VO): A group of individuals or institutions that securely share the computing resources of a “Grid” for a common goal.

Geospatial Grid Service: A Grid service used to processing geospatial data with geospatial standards-compliant interfaces.

Geospatial Grid: The extensions and domain-specific applications of the fundamental Grid computing technology in the geospatial discipline, consisting of serving geospatial data and offering geospatial services.

Grid Service: A processing component in the Grid environment with the WSRF compliant Grid standard interfaces. They can invoke each other in the virtual organization.

Grid Computing: An emerging service-oriented computing model that provides the ability to perform higher throughput and data-intensive computing by securely bringing together geographically and organizationally dispersed computational resources for providing users with advanced ubiquitous distributed sharable computing.

Web Service Resource Framework (WSRF): A specification to provide a clean set of methods to implement stateful web services that communicate with resource services that allow data to be stored and retrieved. It replaces the Open Grid Service Infrastructure (OGSI).

Open Grid Service Architecture (OGSA): An architecture for a service-oriented Grid computing environment for business and scientific use. It is based on several other web service technologies, notably WSDL and SOAP to provide a distributed interaction and computing architecture on heterogeneous systems so that different types of resources can communicate and share information.

Complete Chapter List

Search this Book: