Grid computing

GRID COMPUTING For Documentation and Downloads Visit

ABSTRACT: The Grid means the infrastructure for the Advanced Web, for computing, collaboration and communication. The goal is to create the illusion of a simple yet large and powerful self managing virtual computer out of a large collection of connected heterogeneous systems sharing various combinations of 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 . We presented the Grid concept in analogy with that of an electrical power grid and Grid vision .

INTRODUCTION: These technology opportunities have led to the possibility of using distributed computers as a single, unified computing resource, leading to what is popularly known as Grid computing. The term Grid is chosen as an analogy to a Power Grid that provides consistent, pervasive, dependable, transparent access to electricity irrespective of its source. This new approach to network computing is known by several names, such as metacomputing, scalable computing, global computing, Internet computing , and more recently peer to peer (P2P) computing .

Grid Computing: A Conceptual View The concept of Grid computing started as a project to link geographically dispersed supercomputers, but now it has grown far beyond its original intent. The Grid infrastructure can benefit many applications, including collaborative engineering, data exploration, high-throughput computing, and distributed supercomputing.

What is Grid? “ Resource sharing & coordinated problem solving in dynamic, multi-institutional virtual organizations”.

THE GRID PROBLEM: The real and specific problem that underlies the Grid concept is coordinated resource sharing and problem solving in dynamic, multi-institutional virtual organization s. The sharing that we are concerned with is not primarily file exchange but rather direct access to computers, software, data, and other resources. This sharing is, necessarily, highly controlled, with resource providers and consumers defining clearly and carefully just what is shared, who is allowed to share, and the conditions under which sharing occurs. VOs vary tremendously in their purpose, scope, size, duration, structure, community, and sociology. Business-to-business exchanges focus on information sharing.

THE GRID ARCHITECTURE DESCRIPTION Our goal in describing our Grid architecture is not to provide a complete enumeration of all required protocols but rather to identify requirements for general classes of component. Our architecture and the subsequent discussion organize components into layers, as shown in Figure. Components within each layer share common characteristics but can build on capabilities and behaviors provided by any lower layer. In specifying the various layers of the Grid architecture, we follow the principles of the “hourglass model”.

A p p l i c a t i o n s Diverse global services Local OS

LAYERS OF GRID COMPUTING: FABRIC LAYER: INTERFACES TO LOCAL CONTROL The Grid Fabric layer provides the resources to which shared access is mediated by Grid protocols: for example, computational resources, storage systems, catalogs, network resources, and sensors. the functions implemented at the Fabric level, on the one hand, and the sharing operations supported, on the other. CONNECTIVITY LAYER: COMMUNICATING EASILY AND SECURELY The Connectivity layer defines core communication and authentication protocols required for Grid-specific network transactions. Communication protocols enable the exchange of data between Fabric layer resources. Authentication protocols build on communication services to provide cryptographically secure mechanisms for verifying the identity of users and resources.

RESOURCE LAYER: SHARING SINGLE RESOURCE The Resource layer builds on Connectivity layer communication and authentication protocols to define protocols for the secure negotiation, initiation, monitoring, control, accounting, and payment of sharing operations on individual resources. Resource layer implementations of these protocols call Fabric layer functions to access and control local resources. Two types of resource protocols: Information protocols Management protocols COLLECTIVE: COORDINATING MULTIPLE RESOURCES the architecture contains protocols and services that are not associated with any one specific resource but rather are global in nature and capture interactions across collections of resources. For this reason, we refer to the next layer of the architecture as the Collective layer. Because Collective components build on the narrow Resource and Connectivity layer “neck” in the protocol hourglass, they can implement a wide variety of sharing behaviors without placing new requirements on the resources being shared.

CLUSTER COMPUTING –GRID COMPUTING –INTERNET Cluster computing focuses on platforms consisting of often homogeneous interconnected nodes in a single administrative domain. Application focus is on cycle-stealing computations, high-throughput computations, and distributed computations. Web focuses on platforms consisting of any combination of resources and networks which support naming services, protocols, search engines, etc. Application focus is on access to information, electronic commerce, etc. Grid focuses on ensembles of distributed heterogeneous resources used as a platform for high performance computing. Application focus is on high-performance, resource-intensive applications

THE FUTURE: ALL SOFTWARE IS NETWORK- CENTRIC We don’t build or buy “computers” anymore, we borrow or lease required resources A “computer” is a dynamically, often collaboratively constructed collection of processors, data sources, sensors, networks. Similar observations apply for software. And Thus …  Reduced barriers to access mean that we do much more computing, and more interesting computing, than today => Many more components (& services); massive parallelism  All resources are owned by others => Sharing (for fun or profit) is fundamental; trust, policy, negotiation, payment.  All computing is performed on unfamiliar systems => Dynamic behaviors, discovery, adaptivity, failure.

BENEFITS OF GRID COMPUTING: Organizations can dramatically improve the quality and speed of the products and services they deliver, while reducing IT costs by enabling transparent collaboration and resource sharing. Grid computing enables companies to access and share remote databases. This is especially beneficial to the life sciences and research communities, where enormous volumes of data are generated and analysed during any given day. Grid computing enables widely dispersed organizations to easily collaborate on projects by creating the ability to share everything from software applications and data, to engineering blueprints. Grid computing can create a more robust and resilient IT infrastructure better able to respond to minor or major disasters.

CONCLUSION: Grid computing introduces a new concept to IT infrastructures because it supports distributed computing over a network of heterogeneous resources and is enabled by open standards. Grid computing works to optimize underutilized resources, decrease capital expenditures, and reduce the total cost of ownership. This solution extends beyond data processing and into information management as well. Information in this context covers data in databases, files, and storage devices. In this article, we outline potential problems and the means of solving them in a distributed environment.

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Grid computing

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Grid computing