Abstract: In an increasing number of scientific disciplines, large data collections are emerging as important community resources. Grid computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications, and, in some cases, high performance orientation. The foundation of a grid solution design is typically built upon an existing infrastructure investment. However, a grid solution does not come to fruition by simply installing software to allocate resources on demand. The grid solutions are adaptable to meet the needs of various business problems only because differing types of grids are designed to meet specific usage requirements and constraints. Different topologies are designed to meet varying geographical constraints and network connectivity requirements. The success of a grid solution is heavily dependant on the amount of thought the IT architect puts into the solution design. Harnessing these new technologies effectively will transform scientific disciplines ranging from high-energy physics to the life sciences. . In this paper, we discuss designing of grid along with underlying topologies and models that allow for grid computing to work. Keyword: Virtual organization (VO), Globus tool kit, Grid Security Infrastructure (GSI).
1 Introduction to grid computing
A grid is a collection of machines, sometimes referred to as nodes, resources, members, donors, clients, hosts, engines, and many other such terms. They all contribute any combination of resources to the grid as a whole. Grid computing is an emerging computing model that provides the ability to perform higher
throughput computing by taking advantage of many networked
computers to model a virtual computer architecture that is able to distribute process execution across a parallel infrastructure. Grids use the resources of many separate computers connected by a
network to solve large-scale computation problems . Grids provide the ability to perform computations on large data sets, by breaking them down into many smaller ones, or provide the
ability to perform many more computations at once than would be possible on a single computer, by modeling a parallel division of labor between processes. Grid computing involves sharing
heterogeneous resources located in different places belonging to different administrative domains over a network using open
standards. In short, it involves virtualizing computing resources. Grid computing is often confused with cluster computing. The key difference is that a cluster is a single set of nodes sitting in one location, while a Grid is composed of many clusters and
other kinds of resources. Grid computing reflects a conceptual framework rather than a physical resource. The Grid approach is utilized to provision a computational task with administrativelydistant resources. The focus of Grid technology is associated
with the issues and requirements of flexible computational
provisioning beyond the local administrative domain. A Grid
environment is created to address resource needs. The use of that resource is usually characterized by its availability outside of the context of the local administrative domain. This 'external
provisioning' approach entails creating a new administrative domain referred to as a Virtual Organization (VO) with a distinct and separate set of administrative policies The context for a Grid 'job execution' is distinguished by the requirements created when operating outside of the home administrative context. Grid
technology is employed to facilitate formalizing and complying with the Grid context associated with your application execution .
2. Building grid architecture
Once the functional and non-functional requirements are known, the IT architect should readily be able to select the type of grid and the best topology required to satisfy the majority of the business...
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