Grid Computing: Technicalities and Overview

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

© World Scientific Publishing Company ON THE CONVERGENCE OF COMPUTATIONAL AND DATA GRIDS

Great advances in high-performance computing have given rise to scientific applications that place large demands on software and hardware infrastructures for both computational and data services. With these trends the necessity has emerged for distributed systems developers that once distinguished between these elements to acknowledge that indeed computational and data services are tightly coupled and need to be addressed simultaneously. In this article, we compile and discuss several strategies and techniques, like co-scheduling and co-allocation of computational and data services, dynamic storage capabilities, and quality-of-service, that can be used to help resolve some of the aforementioned issues. We present our interactions with a distributed computing system, NetSolve, and a Distributed Storage Infrastructure, IBP, as a case study of how some of these techniques can be effectively deployed and offer experimental evidence from early prototypes that validate our motivation and direction