GRID COMPUTING TECHNOLOGIES
S.Gowri
1, N.Ramadevi
2, S.Vijayalakshmi
31
Head of the Department, Department of Computer Applications,
Dhanalakshmi Srinivasan College of Arts and Science for Women, Perambalur (India)
2,3
M.C.A., DIY., Department of Computer Applications,
Dhanalakshmi Srinivasan College of Arts and Science for Women, Perambalur (India)
ABSTRACT
The development of grid computing approach the end user will be ubiquitously offered any of the services of a
“grid” or a network of computer systems located in a Local Area Network(LAN) or a Wide Area Network (WAN) in a spread of geographical area it aims at dynamic or “Runtime” selection, allocation and control of computational resources such as processing power, disk storage or specialized software systems. This can be done according to the demands of the end users. Grid computing also the way end-users of a power supply or a water supply grid connect and draw power or water as they need, at any time and any location without any knowledge or reference to the details.
Keywords: Grid Computing, Grid Data, Distributed Systems.
I. INTRODUCTION
A grid is a collection of distributed computing resources over a local or wide area network, that appear to an end-user or application as one large virtual computing.Grid computing is to create virtual dynamic organizations through secure, co-ordinated resource sharing among individuals and institutions. Grid computing is an approach in distributed computing that spans locations, sharing among individuals and institutions. Grid computing is an approach in distributed computing that spans locations, organizations, machine architecture and software boundaries to provide unlimited power, collaboration and information access to everyone connected to the grid. The internet is about getting computers to gather (connected), grid computing is about getting computers work together. The grid computing middleware software will manage and execute all the activities related to identification, allocation, de-allocation and, allocation, de-allocation and consolidation of all the resources to the end-users transparently, as in the case of a power supply grid. On the internet, the world‟s largest network, if a grid of all computers is established, then the Internet will offer the world‟s largest virtual computer on service to the internet users.
It is not enough to have all the world‟s computers connected together to make a grid-It is also essential to have the management software to operate on this grid so as to make available a variety of resources to the end-users of the Internet, as and when users requires it, located anywhere in the world.The Globus Alliance, a research and development initiative, focused on enabling the application of grid technology to scientific and technological domain computing.
Definition :
A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive and expensive access to high end computational capabilities.II.ABOUT THE TECHNOLOGY
The grid computing came about, individual data centres had been operationalized.Before the data centre came about, each user organization maintained it‟s own servers and it‟s own specialized software-an expensive and redundant approach.Data Centres eliminated the need for separate servers being maintained by the individual user organizations-they share the data centre resources.
However, individual data centres may not necessarily maintain and offer all the possible resources-hardware or software. The user organizations or individual users connected to a simple data centre may be able to use the resources available in that particular data centre, belonging to a different organization. The concept of grid computing enables multiple data centres of same or different organizations to be networked into a grid, so as to offer all the resources of hardware and
software, in all data centres to any of the users of any of these multiple organizations, however remote they may be.
Grid computing includes concepts of distributed computing, and disposable computing, depending upon the exact nature and scale of the application of the grid. Infact, a virtual super computer can be created out of a grid, comprising of it‟s servers, workstations and even PCs to deliver higher processing power.
Figure1:Structure of Grid computing
Thus, the grid can provide a meta computing environment, which can be a mega computing facility for the users, by treating CPU power, disk space, bandwidth as commodity to be utilized by the users of the grid, as and when they require. Just as utilizing the grids of power, water, etc. Provides a consumable utility to the consumers, the grid computing will provide a computational utility to it‟s consumers.
2.1 Recent Technological Trends in Large Data Grids
Data grids are required to be handled with middleware products. The GGF working group report on data middleware has defined the facilities to be provided for the data management in the middleware. Storage Report
Broker(SRB) of European Data Grid middleware are such middleware. For peta scale data grids Datafarm architecture is proposed.
Figure2: Grid Architecture
2.2 The Data farm Architecture for Global Large (Petabytes) Scale Data Grids
The grids become global, we have very large petascale data volumes that required handling only grid. Recent research in the Japan has brought out advanced, movel techniques such as Datafarms architecture for petascale data grids.
Grid Data Farm
Gfarm is defined for global, petascale, data intensive computing. It aims at providing a global, parellal file system, with online peta scale storage, along with scalable I/O bandwidth, and also reliable parallel processing
III. COMPARISONS
Grid computing can also compared with cluster, web services, e-Governance etc.
Cluster Computing and Grid Computing
Scientific, Business and e-Governance Grids
Web Services and Grid computing
e-Governance and the Grid
3.1 Cluster Computing and Grid Computing
Clusters are aggregations of processors in parallel configurations. In clusters, the resource allocation is performed by a centralized resource manager and scheduling system. All the nodes of a cluster work co- operatively together, as a single unified resource.
In the case of grid, each node has it‟s own resource manager and it does not aim at providing a single system view.
A cluster comprises of multiple inter-connected independent nodes that co-operatively work together as a single unified resource.
Some grids are collections of clusters e.g., NSF Tera grid and world wide grid which has several clusters as nodes located in different countries (Canada and Japan).
3.2 Scientific, Business and e-Governance Grids
In scientific grids the users may be only the scientists belonging to scientific organizations; In the case of business grids or e-governance grids, the users may belong to any citizen groups using business services or government services. The number of such users can be very large, compared to the restricted users of scientific grids.
Therefore, the challenges of setting up and operating business grids or e-governance grids are different and much greater than those for setting up scientific grid computing environments. The number of citizens being very large, Internet is the only communication network available to the citizens for accessing a business grid or an e-governance grid. The user interfaces, the access speeds and the data sizes will be large.
3.3 Web Services and Grid Computing
The users of such grids viz. citizens, will required web services over the Internet. They will not be interested or required to know of any details of hardware or software resource locations or resource allocation management.
All this has to be provided by the grid computing environment.
Thus, integrating web services with grid architecture becomes a necessity for these purposes. The Open Grid Services Architecture(OGSA) becomes essential to offer effective, stateful web services based on Service Oriented Architecture(SOA) on the grid.
3.4 e-Governance and the Grid
e-governance is also a potential application of grid computing g on the lines similar to e-business. All the consideration described for the business world are also applicable to government. In the e-governance, the citizen becomes the end-user, and high priority application of the grid. Citizen services are delivered as e- governance services through the web.
Presently, most of the e-governance services are only web-enabled services. The new paradigm of technology being web services based on the Service Oriented Architecture(SOA), the e-governance services also should be delivered as web services, a change presently underway. Then e-governance services are delivered as web services(on SOA), the grid has to support the web services, as the resources required by a large number of web services call for robust computing infrastructure such as the grid.
Figure3:Structure of e-Governance
IV. STANDARDS OF GRID COMPUTING
The need and necessity of standards is felt most integrated environment, as the grid, by it‟s very nature, is comprised of heterogeneous hardware, operating systems, software platforms, etc.
Considering the interoperability requirements of a grid, the standards grid computing should be open standards, with general purpose protocols and interfaces. Grid standards are being defined, accepted and implemented by the vendors globally.
First Generation Grids(1G)
Second Generation Grids(2G)
Third Generation Grids(3G)
The standards based grids are termed third generation of 3G grids. The first generation grids where just local language meta computers, with basic distributed servers such as distributed file system, single sign-on based distributed application and customer communication protocols.
Figure4: Grid generations
Later 1G grids got extended across long distances, and also explored the interorganizational issues. The 2G grids came up as an improvement, with projects such as Candor and I-Way or Legion, in all of which the underlying communication protocols software services could be used for developing distributed application and services.
2G grids only offers a very basic core/kernel and application development which require significant customization efforts. Thus 2G grids were not easily interoperable. Then came 3G grids, with standards for interoperability. 3G technology, the latest standards of grid technology, enables not only interoperability between application and toolkits, but even implementation of key services. This will also promotes healthy competition amongst vendors, who develop grid toolkits and applications.
V. ISSUES IN GRID COMPUTING
Grid computing, also known as e-Science, has also been concerned deeply with data-large volume of data, upto peta bytes, have to be managed. For example, in particle physics research, special techniques such as grid data farms have been developed to handle such large scale data, with several peta bytes of data being produced per year.
In the commercial domain also, data grids have been built and used. In banking and financial sector, huge amounts of data need to be processed, data warehousing and data mining being some of the users of this data can be put to Grid technology offers solutions for managing and maintaining such large volumes of data, making it readily available for data mining.
The influence and combination of large data sizes on one hand and large spread of geographical distribution of the users and the resources and analytic exercises on data on the other, have prompted the development of data grids[2].
In the Global Grid Forum (GGF) working group report, a data middleware, as part of the grid middleware software, has been defined to provide facilities for data management. Data middleware approaches, which are successful, include Storage Resource Broker (SRB)[3], Grid Data Farm[4] and the European Data Grid
Middleware. All such approaches of a novel techniques for large and very large data management for a grid (They not be compatible with each other).
VI. CONCLUSION
Linking geographically dispersed computer systems can lead to staggering gains in computing power, speed and productivity. Computers within a grid system can be either hardwired together or run on open system that connect with each other via the web they can also running the same operating system(Homogeneous system) or on different operating systems (Hetrogeneous system).
Networks are constructed with the aid of general purpose grids software libraries(“middleware”) that allow computers the ability to run a process or series of applications across the entire network of machines. Without it, communication across the system would be impossible. Computers can be purchased separately as commodity hardware, but when combined, provide a business with all of the functionality of a super computer. Grid computing systems provide business with a quick, low-power avenue to complicated solutions. Available resources are maximized and the fact that users are able to run parallel operations saves time, too. Grid technologies overcame these obstacles and problems by providing standard and uniform mechanisms for critical tasks such as creating and managing services on remote computers, for supporting remote „Single Sign On‟ to distribute resources.
REFERENCE
[1]. C.S.R Prabhu, “Grid and cluster computing “January 2009 [2]. http://www.globus.org
[3]. https://www.worldcommunitygrid .org
[4]. T.Hawk.,” Remarks On Grid Computing”, June 2002 [5]. http:www.gridcomputing.com
[6]. http:www.opensciencegrid.org [7]. http:www.researchgate.net [8]. https://twiki.grid.iu.edu
BIBLIOGRAPHY NOTE
Mrs.S.Gowri -Received MS(IT)., M.Phil., Degree in Computer Science. She has 10 years of Teaching Experience. She had presented 5 papers in International Conference and also she presented 4 paper in National Conference. She also published one paper in IJSTM. She is currently working as Assistant Professor in Department of Computer Applications in Dhanalakshmi Srinivasan College of Arts and Science for Women, Perambalur, Tamil Nadu, India.
Ms. N.Ramadevi - PG scholar, [Department of CA] ,Pursuing M.C.A Computer Applications in Dhanalakshmi Srinivasan College of Arts & Science for women, Perambalur-621212, TamilNadu, (India).
Ms .S.Vijayalakshmi - PG scholar, [Department of CA] ,Pursuing M.C.A Computer Applications in Dhanalakshmi Srinivasan College of Arts & Science for women, Perambalur-621212, TamilNadu, (India).
