International Journals of Advanced Research in June Science and Software Engineering Research Article 2017 ISSN: 2277-128X (Volume-7, Issue-6)

Grid Computing Matthew N.O. Sadiku1, Adebowale E. Shadare2, Sarhan M. Musa3 1, 2Department of Electrical & Computer Engineering, 3Department of Engineering Technology, Prairie View A&M University, Prairie View, TX 77446, United States DOI: 10.23956/ijarcsse/V7I6/01612

Abstract - Grid computing refers to a distributed architecture of a large number of connected to solve a complex problem. It allows the computers on the network to work on a task together, behaving like a . The major advantage of grid computing is that it reduces the time taken to complete tasks, without increasing costs.This paper provides a brief introduction to grid computing.

Keywords: grid computing,

I. INTRODUCTION The availability of powerful computers and high-speed computer networks such as the is changing the way computing is done. These new technologies have led to all kinds of computing such as , distributed computing, , , cluster computing, mobile computing, and grid computing. The term “grid computing” was first used in the early 1990s as a metaphor for making computer power as easy to access as an electric power grid. It was first established in the early 1990s by Carl Kesselman, Ian Foster and Steve Tuecke, who are widely regarded as the “fathers of the grid.” Grid computing was inspired by the electrical power grid. It involves computation in a distributed manner. Grid technologies leverage the computational power of the available computers by managing them in the grid infrastructure. Grid or distributed computing is a special type of parallel computing that relies on complete computers connected to a . The grid may be small or large [1]. A grid consists of parallel nodes that form a , which runs on an . Different forms of grids now exist including power grids, computational grids, access grids, and data grids. Computers on a grid may not be in the same geographical location, and can be spread out over many countries and owned by several organizations with different policies. The computing grid integrates networking, computation and information to provide a virtual platform for computation and data management infrastructure that provides the electronic foundation for operating in business, government, research, science and entertainment. Grid computing is a computer network in which every computer can access the resources of every other computer connected to the network. Enormous processing power, memory and are resources that authorized users can leverage for performing specific tasks. A grid architecture is shown in Figure 1 [2]. The benefits of grid computing include effective use of resources, save processing time, improves methods for collaborative work, and resource balancing and reliability [3].

II. APPLICATIONS Grid computing is the technology for sharing distributed resources at the large-scale, which is accomplished in a transparent and location-independent way. It allows users to effortlessly take advantage of the vast computational resources available on the grid by simply plugging applications into it. Grid-enabled applications are specific software applications that can utilize grid infrastructure. Grid computing has attracted worldwide attention in various grand-challenge data intensive applications ranging from physics, chemistry, environment, engineering, commerce, aerospace, and healthcare. It offers a way to solve tough problems such as protein folding, financial modeling, earthquake simulation, and weather modeling. Several grid projects exist that support different applications from different disciplines including arts and humanities.

Figure 1. Grid protocol architecture [2]. © www.ijarcsse.com, All Rights Reserved Page | 5 Sadiku et al., International Journals of Advanced Research in Computer Science and Software Engineering ISSN: 2277-128X (Volume-7, Issue-6) III. CHALLENGES Grid computing is currently not broadly accessible to non-computing users and continues to be user unfriendly. Grid computing systems are complex and therefore require appropriate automated management. Such heterogeneous systems require proper attention be given to security of the data because interactions of resources make the systems vulnerable. The necessary security measures are usually specified in terms of authentication, authorization, resource protection, secure communication, data confidentiality, data integrity, and policy management [4]. The success of grid computing depends on issues in five main areas: economics, security, performance, reliability, and standards. In order for organizations to adopt the grid computing model, there needs to be a reliable set of standards and protocols in place. At the moment, grid computing systems rely on proprietary tools. Researchers are still working on establishing standards and protocols. Security is an issue with grids, because the controls on member nodes are usually loose; it is highly probable that some number of compute nodes will disconnect or fail. In order for grid technology to continue to grow, grid systems must provide high reliability. Although there are shortcomings in current grid computing systems, the concept remains valid and can benefit from new developments such as cloud computing. It is wrong to consider cloud computing as a competitor to grid computing as both approaches can benefit from each other [5].

IV. CONCLUSION Grid computing is far from being mature. It did not enter the mainstream of research until 1998 when the establishment of the Global Grid Forum (www.gridforum.org) was made. Grid computing is standardized by the Global Grid Forum and applied by the Globus Alliance (http://www.globus.org/about/). Wireless grids extend the capability of grid computing to wireless devices such sing laptops, PDAs, and cell phones. Mobile grid computing is an extension to grid computing [6].

REFERENCES [1] “Grid computing,” Wikipedia, the free encyclopedia https://en.wikipedia.org/wiki/Grid_computing [2] I. Foster et al., “Cloud Computing and Grid Computing 360-Degree Compared,” Grid Computing Environments Workshop, pp. 1-10, 2008. [3] H. Setial and A. Jain, “Literature survey on various scheduling approaches in grid computing environment,” Proceedings of 1st IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems, 2016. [4] J. C. Patni et al., “Methods and mechanisms of security in grid computing,” Proceedings of the 2nd International Conference on Computing for Sustainable Global Development, pp.1040-1043, 2015. [5] U. Schwiegelshohn et al., “Perspectives on grid computing,” Future Generation Computer Systems, vol. 26, pp. 1104-1115, 2010. [6] S. S. Manvi and M. N. Birje, “Wireless grid computing: A survey,” IETE Journal of Education, vol. 50, no. 3, pp.119-131, 2009.

ABOUT THE AUTHORS

Matthew N.O. Sadiku is a professor at Prairie View A&M University, Texas. He is the author of several books and papers. He is an IEEE fellow. His research interests include computational electromagnetics and computer networks. Adebowale Shadare is a doctoral student at Prairie View A&M University, Texas. He is the author of several papers. His research interests are in the area of smart grid EMC, computational electromagnetics and computer networks. Sarhan M. Musa is a professor in the Department of Engineering Technology at Prairie View A&M University, Texas. He has been the director of Prairie View Networking Academy, Texas, since 2004. He is an LTD Spring and Boeing Welliver Fellow.

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