Grid Computing Technology

Future Generation Computer Systems, 2002

As the practice of science moves beyond the single investigator due to the complexity of the problems that now dominate science, large collaborative and multi-institutional teams are needed to address these problems.

Future Generation Computer Systems, 2008

This special issue of Future Generation Computer Systems is devoted to modern applications of distributed and grid computing. A relatively small number of papers were selected in order to cover some important areas of distributed and grid computing. At the same time we do not pretend that all important areas of this fast developing scientific field are covered.

arXiv (Cornell University), 2012

The evolution of the global scientific cyberinfrastructure (CI) has, over the last 10+ years, led to a large diversity of CI instances. While specialized, competing and alternative CI building blocks are inherent to a healthy ecosystem, it also becomes apparent that the increasing degree of fragmentation is hindering interoperation, and thus limiting collaboration, which is essential for modern science communities often spanning international groups and multiple disciplines (but even 'small sciences', with smaller and localized communities, are often embedded into the larger scientific ecosystem, and are increasingly dependent on the availability of CI.) There are different reasons why fragmentation occurs, on technical and social level. But also, it is apparent that the current funding model for creating CI components largely fails to aid the transition from research to production, by mixing CS research and IT engineering challenges into the same funding strategies. The 10 th anniversary of the EU funded project 'Grid Lab' (which was an early and ambitious attempt on providing a consolidated and science oriented cyberinfrastructure software stack to a specific science community) was taken as an opportunity to invite international leaders and early stage researchers in grid computing and e-Science from Europe, America and Asia, and, together with representatives of the EU and US funding agencies, to discuss the fundamental aspects of CI evolution, and to contemplate the options for a more coherent, more coordinated approach to the global evolution of CI.

International Journal of Research Publications in Engineering and Technology [IJRPET], 2017

The last some years there has been a rapid rampant increase in computer processing power, communication, and data storage. Grid is an infrastructure that contains the integrated and collective use of computers, databases, networks and experimental instruments managed and owned by various organizations. Grid computing is a kind of distributed computing whereby a "super and virtual computer" is built of a cluster of networked, loosely coupled computers, working in concert to perform large tasks. Here paper presents an introduction of Grid computing providing wisdom into the gird components, terms, architecture, Grid Types, Applications of grid computing.

2002

In the last few years there has been a rapid exponential increase in computer processing power, data storage and communication. But still there are many complex and computation intensive problems, which cannot be solved by supercomputers. These problems can only be met with a vast variety of heterogeneous resources. The increased use and popularity of the Internet and the availability of high-speed networks have gradually changed the way we do computing. These technologies have enabled the cooperative use of a wide variety of geographically distributed resources as a single more powerful computer. This new method of pooling resources for solving large-scale problems is called as grid computing. Grid computing is a form of distributed computing in which an organization (business, university, etc.) uses its existing computers (desktop and/or cluster nodes) to handle its own long-running computational tasks. Grid computing combines computers from multiple administrative domains to reach a common goal, to solve a single task, and may then disappear just as quickly. Grid computing is managed by Global Grid Forum (GGF). Grid includes various protocols, topologies, standards and layers for implementing grid related applications. This paper describes the concepts underlying grid computing.

2008

The European Grid Initiative (EGI) represents an effort to realize a sustainable grid infrastructure in Europe and beyond. Based on the requirements of the user communities and by combining the strength and views of the National Grid Initiatives (NGI), EGI is expected to deliver the next step towards a permanent and common grid infrastructure. The effort is currently driven by the EGI Design Study, an FP7 funded project defining the structure and functionality of the future EGI and providing support to the NGIs in their evolution. The goal is the setup of an organizational model, with the EGI Organization (EGI.org) as the glue between the national efforts, which provides seamless access to grid resources for all application domains.

2009

Abstract We review the impact of Grid Computing and Web Services on scientific computing, stressing the importance of the “data-deluge” that is driven by deployment of new instruments, sensors and satellites. This implies the need to integrate the naturally distributed data sources with large simulation engines offering parallel low latency communication and so to integrate parallel and Grid computing paradigms. We start with an overview of these and the evolving service architectures.

Proceedings of the …, 2000

We use the term "Grid" to refer to a software system that provides uniform and location independent access to geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. While, in general, Grids will provide the infrastructure to support a wide range of services in the scientific environment (e.g. collaboration and remote instrument control) in this paper we focus on services for high performance computing and data handling. We describe the services and architecture of NASA's Information Power Grid ("IPG") -an early example of a large-scale Grid -and some of the issues that have come up in its implementation.

Concurrency and Computation: Practice and Experience, 2010

In the recent decades we have witnessed a major revolution in the computer field. The major challenges posed by applications in fields of bioinformatics, earth sciences or weather forecasting, among others, have caused the proliferation of complex solutions, such as grid, cloud and highperformance computing. The common objective of all these disciplines is the sharing of hardware and software resources to provide an infrastructure in which to run efficiently these applications. Particularly, grid computing has been one of the most important computing topics in the last years. Within this context, the GADA workshop arose in 2004 as a forum for researchers in grid computing and its application to data analysis. From then until 2008, GADA became a reference conference for researchers in grid, covering also a broader set of disciplines, although grid computing continued to play a key role in the set of main topics of the conference.

Proceedings. The Eighth International Symposium on High Performance Distributed Computing (Cat. No.99TH8469), 1999

Abstract Applications designed to execute on “computational grids” frequently require the simultaneous co-allocation of multiple resources in order to meet performance requirements. For example, several computers and network elements may be required in order to achieve real-time reconstruction of experimental data, while a large numerical simulation may require simultaneous access to multiple supercomputers. Motivated by these concerns, we have developed a general resource management architecture for Grid environments, in ...

In this paper, we studied about the grid computing, benefits and applications of grid computing. Grid computing is still a developing field. Grid computing is used to solve complex problem in a simple manner by sharing resources with each other.

Grid computing is a technology about the sharing of distributed resources and integration system at a large scale. Grid computing is the mainstream technology for the resource sharing and system at the large-scale. Grid computing is specially made for scientific application but now a day is becoming important model in the commercial application. To understand the grid working we described the architecture main theme of grid computing is the grid control protocol which described the structure of grid computing. Grid protocol has the five layers. A comprehensive grid computing analyzed by regarding selfish grid computing in grid selfish behavior of machine can damage performance as the whole. A hierarchical game model of grid is presented that machine in real life with the structure of physical. A hierarchical structure is used in the management of scalability of grid. In grid we define the scalability by the scalability management. In this paper we analyzed the genetic algorithm that is based on schedulers for allocating jobs to resources efficiently in the grid computing. This algorithm assigns the jobs to resources with efficiency in the Grid computing.

A scientist studying proteins logs into a computer and uses an entire network of computers to analyze data. A businessman accesses his company's network through a PDA in order to forecast the future of a particular stock. An Army official accesses and coordinates computer resources on three different military networks to formulate a battle strategy. All of these scenarios have one thing in common: They rely on a concept called grid computing. At its most basic level, grid computing is a computer network in which each computer's resources are shared with every other computer in the system. Processing power, memory and data storage are all community resources that authorized users can tap into and leverage for specific tasks. A grid computing system can be as simple as a collection of similar computers running on the same operating system or as complex as inter-networked systems comprised of every computer platform you can think of.

Lecture Notes in Computer Science, 2004

The use of grid computing technology is being boosted in last years by the growing demand of low cost computing resources and idle computing capacity in collaborative research and development environments. GridBR is a PETROBRAS project done with the collaboration of COPPE/UFRJ and IBM Brazil partnership. This project aims at grid computing technology in the information technology strategy of PETRO-BRAS Research and Development Center (CENPES). The present environment comprises a heterogeneous mix of architectures and operating systems with AIX IBM and Linux workstations providing the required support for collaborative execution of applications. The results of a genetic algorithm optimization application are presented as an example of how to take advantage of the existing grid computing infrastructure at PETROBRAS.