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ABSTRACT
“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 .In this technical paper we presented this new type of computing. First we reviewe the problem which we define as flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions, and resources—what we refer to as virtual organizations. In such settings, there encounter unique authentication, authorization, resource access, resource discovery, and other challenges. It is this class of problem that is addressed by Grid technologies. We presentedmm the Grid concept in analogy with that of an electrical power grid and Grid vision We also discussed the reason why grids are needed and why now we are concentrating on this Grid computing .Next, we present an extensible and open Grid architecture, in which protocols, services, application programming interfaces, and software development kits are categorized according to their roles in enabling resource sharing. We also describe requirements that must satisfy and also protocols to provide interoperability among different Grid systems . We also compared the Grid computing with that of Cluster computing and Internet. Finally we present a brief introduction about the successful Grid technology GLOBUS toolkit a defacto standard for major protocols and services. We have been part of Grid network whose main target is to cure cancer and also trying to be part of another grid network which concentrates on SETI(Search of Extraterrestrial Intelligence)..

INDEX



1. Introduction
1.1Grid Concept and Grid Vision
2. What is Grid?
3. The Grid problem
4. Why Grids and Why now?
5. The Grid Architecture Description
5.1 Fabric Layer: Interfaces To Local Control
5.2 Connectivity Layer: Communicating Easily and Securely
5.3 Resource Layer: Sharing Single Resource
5.4 Collective: Coordinating Multiple Resources
6. Cluster Computing –Grid Computing –Internet
7. The Future: All Software is Network- Centric
8. Benefits of Grid Computing
9. Summary







1. INTRODUCTION:
The term “THE GRID” was coined in the mid1990’s to denote a proposed distributed computing infrastructure for advanced science and engineering. Considerable progress has since been made on the construction of such an infrastructure, but the term “Grid” has also been conflated, at least in popular perception, to embrace everything from advanced networking to artificial intelligence. One might wonder whether the term has any real substance and meaning. Is there really a distinct “Grid problem” and hence a need for new “Grid technologies”? If so, what is the nature of these technologies, and what is their domain of applicability? While numerous groups have interest in Grid concepts and share, to a significant extent, a common vision of Grid architecture, we do not see consensus on the answers to these questions.
Our purpose in this article is to argue that the Grid concept is indeed motivated by a real and specific problem and that there is an emerging, well-defined Grid technology base that addresses significant aspects of this problem. In the process, we develop a detailed architecture and roadmap for current and future Grid technologies. Furthermore, we assert that while Grid technologies are currently distinct from other major technology trends, such as Internet, enterprise, distributed, and peer-to-peer computing, these other trends can benefit significantly from growing into the problem space addressed by Grid technologies.
1.1 GRID CONCEPT AND GRID VISION
The following are points to be noted when comparing our Grid with that of a power grid.
• “On-demand” access to ubiquitous distributed computing
• Transparent access to multi-petabyte distributed data bases
• Easy to plug resources into
• Complexity of the infrastructure is hidden
“When the network is as fast as the computer's internal links, the machine disintegrates across the net into a set of special purpose appliances”
E-Science and information utilities (Taylor)
• Science increasingly done through distributed global collaborations between people, enabled by the Internet
• Using very large data collections, terascale computing resources, and high performance visualisation
• Derived from instruments and facilities controlled and shared via the infrastructure
• Scaling x1000 in processing power, data, bandwidth
2. What is Grid?
“Resource sharing & coordinated problem solving in dynamic, multi-institutional virtual organizations”.



3. 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 organizations. The sharing that we are concerned with is not primarily file exchange but rather direct access to computers, software, data, and other resources, as is required by a range of collaborative problem-solving and resource-brokering strategies emerging in industry, science, and engineering. 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. A set of individuals and/or institutions defined by such sharing rules form what we call a virtual organization (VO).
VOs vary tremendously in their purpose, scope, size, duration, structure, community, and sociology. Nevertheless, careful study of underlying technology requirements leads us to identify a broad set of common concerns and requirements. In particular, we see a need for highly flexible sharing relationships, ranging from client-server to peer-to-peer; for sophisticated and precise levels of control over how shared resources are used, including fine-grained and multi-stakeholder access control, delegation, and application of local and global policies; for sharing of varied resources, ranging from programs, files, and data to computers, sensors, and networks; and for diverse usage modes, ranging from single user to multi-user and from performance sensitive to cost-sensitive and hence embracing issues of quality of service, scheduling, co-allocation, and accounting.
Current distributed computing technologies do not address the concerns and requirements just listed. For example, current Internet technologies address communication and information exchange among computers but do not provide integrated approaches to the coordinated use of resources at multiple sites for computation. Business-to-business exchanges focus on information sharing (often via centralized servers).
4. WHY GRIDS AND WHY NOW?
• A biochemist exploits 10, 000 computers to screen 100,000 compounds in an hour
• 1,000 physicists worldwide pool resources for petaop analyses of petabytes of data
• Civil engineers collaborate to design, execute, & analyze shake table experiments
• Climate scientists visualize, annotate, & analyze terabyte simulation datasets
• An emergency response team couples real time data, weather model, population data
• A multidisciplinary analysis in aerospace couples code and data in four companies
• A home user invokes architectural design functions at an application service provider
• Scientists working for a multinational soap company design a new product
• A community group pools members’ PCs to analyze alternative designs for a local road
Why Now?
The following are the reasons why now we are concentrating on Grids:
• Moore’s law improvements in computing produce highly functional end systems
• The Internet and burgeoning wired and wireless provide universal connectivity
• Changing modes of working and problem solving emphasize teamwork, computation
• Network exponentials produce dramatic changes in geometry and geography
The network potentials are as follows:
Network vs. computer performance
• Computer speed doubles every 18 months
• Network speed doubles every 9 months
• Difference = order of magnitude per 5 years
A comparison of networks vs Computer performance from 1986 to 2000 is as follows:
The Computers performance is increased 500 times where as Network performance is increased by 340,000 times.
5.THE GRID ARCHITECTURE DESCRIPTION
Our goal in describing our Grid architecture is not to provide a complete enumeration of all required protocols (and services, APIs, and SDKs) but rather to identify requirements for general classes of component. The result is an extensible, open architectural structure within which can be placed solutions to key VO requirements. 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 behaviours provided by any lower layer. In specifying the various layers of the Grid architecture, we follow the principles of the “hourglass model”. The narrow neck of the hourglass defines a small set of core abstractions and protocols (e.g., TCP and HTTP in the Internet), onto which many different high-level behaviours can be mapped (the top of the hourglass), and which themselves can be mapped onto many different underlying technologies (the base of the hourglass).
A p p l i c a t i o n s Diverse global



services core services


Local OS




5.1 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. A “resource” may be a logical entity, such as a distributed file system, computer cluster, or distributed computer pool; in such cases, a resource implementation may involve internal protocols.
There is thus a tight and subtle interdependence between the functions implemented at the Fabric level, on the one hand, and the sharing operations supported, on the other.

5.2 CONNECTIVITYLAYER: 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.
Communication requirements include transport, routing, and naming. While alternatives certainly exist, we assume here that these protocols are drawn from the TCP/IP protocol stack: specifically, the Internet (IP and ICMP), transport (TCP, UDP), and application (DNS, OSPF, RSVP, etc.) layers of the Internet layered protocol architecture
5.3 RESOURCE LAYER: SHARING SINGLE RESOURCE
The Resource layer builds on Connectivity layer communication and authentication protocols to define protocols (and APIs and SDKs) 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. Resource layer protocols are concerned entirely with individual resources and hence ignore issues of global state and atomic actions across distributed collections; such issues are the concern of the Collective layer discussed next.
Two primary classes of Resource layer protocols can be distinguished:
• Information protocols are used to obtain information about the structure and state of a
resource, for example, its configuration, current load, and usage policy (e.g., cost).
• Management protocols are used to negotiate access to a shared resource, specifying, for example, resource requirements (including advanced reservation and quality of service) and the operation(s) to be performed, such as process creation, or data access. Since management protocols are responsible for instantiating sharing relationships, they must serve as a “policy application point,” ensuring that the requested protocol operations are consistent with the policy under which the resource is to be shared. Issues that must be considered include accounting and payment. A protocol may also support monitoring the status of an operation and controlling (for example, terminating) the operation.
5.4 COLLECTIVE: COORDINATING MULTIPLE RESOURCES
While the Resource layer is focused on interactions with a single resource, the next layer in the architecture contains protocols and services (and APIs and SDKs) 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.
6. CLUSTER COMPUTING –GRID COMPUTING –INTERNET
Cluster computing focuses on platforms consisting of often homogeneous interconnected nodes in a single administrative domain.
• Clusters often consist of PCs or workstations and relatively fast networks
• Cluster components can be shared or dedicated
• 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.
• Web consists of very diverse set of computational, storage, communication, and other resources shared by an immense number of users
• 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.
• Some grid resources may be shared, other may be dedicated or reserved
• Application focus is on high-performance, resource-intensive applications
7. THE FUTURE: ALL SOFTWARE IS NETWORK- CENTRIC
• We don’t build or buy “computers” anymore, we borrow or lease required resources
o When I walk into a room, need to solve a problem, need to communicate
• A “computer” is a dynamically, often collaboratively constructed collection of processors, data sources, sensors, networks
o 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.
8. BENEFITS OF GRID COMPUTING
• Grid computing enables organizations to aggregate resources within an entire IT infrastructure no matter where in the world they are located. It eliminates situations where one site is running on maximum capacity, while others have cycles to spare.
• 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.
• A grid can harness the idle processing cycles that are available in desktop PCs located in various locations across multiple time zones. For example, PCs that would typically remain idle overnight at a company's Tokyo manufacturing plant could be utilized during the day by its North American operations.
9. SUMMARY
• The Grid problem: Resource sharing & coordinated problem solving in dynamic, multi- institutional virtual organizations
• Grid architecture: Emphasize protocol and service definition to enable interoperability and resource sharing.