Challenges and advantages of grid computing

Challenges and advantages of grid computing

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  Prof. Neeraj Bhargava PoojaDixit Department of Computer Science School of Engineering & System Sciences MDS, University Ajmer, Rajasthan, India 1
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  A lot ofheterogeneous hardware is used in order to create the Grid and, in addition, these devices are not managed by only one person but by different system administrators in each of the companies. Grid follows the challenges that need to be resolved to harness the full power of grid:-  No clear standard:-Grid computing uses various standards, but all grids are not use same standards. Example all grid operating system such as Linux, Apache and My SQL are using WSRF, UDDI, WWW, SOAP and XML standards. Oracle 10g enterprise implement without WSRF. IBM develops the Grid middleware based on J2EE. We cannot use different OS at the same machine in the same time in grid computing.  Distributed computing Vs Grid computing: - Grid computing involves dynamic virtual organisation, resource sharing and peer to peer computing. The Grid intends to make access to computing power, scientific data repositories and experimental facilities as easy as the Web makes access to information. Same all facilities provide the grid computing. So it is a challenge for grid computing.  Lack of grid enabled software: - The software, which are enabled the grid computing are less, It has limited software on Grid. Much software has not copyright issues and source code of licence. It is need for more company developing grid-enabled version, need more developers on grid development and need to develop open source software.  Sharing Resources between Various Types of Services:- Grid used for sharing resource from various sites and grid hosts. It handles a massive amount of data as a grid platform. A lot of sites and multiple servers gathered there it is so complex infrastructure. It provides difficulty for hardware resource sharing within virtual organisation.  Difficult to develop: - Grid programming used java, XML, use web services WSDD, WSDL, UDDI, WSRF, and GT3developing guidelines. It is a matter who developing the grid Applications. Basically that is available for senior computer science developers and enterprise developers. 2
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   Limited Area& Applications:-Grid computing is used to solve for large and complex problems. Its area is limited such as scientists, developer, analysis and researchers. Grid computing is used in Hollywood flickers, industrial research, and biometric research and engineering research. Grid cannot use for common problems by common persons.  Management and Administration: - Many institutes and organizations used grid computing. It distributes the resources on large geographically distributed environments and accesses the heterogeneous devices and machines. So it is a major challenge to manage the administration of the grid computing. 3
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   All theresource available in the grid environment are basically owned and managed by multiple organization. For the efficient operation of computational grid various factors must be considered such as resources sharing, and load balancing etc. The primary challenges that should be taken into account for grid system are as followed:  Administration & Security  Solution Development  Resource heterogeneity  Accounting infrastructure  Programming for application development  Resource Management 4
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   Exploiting underutilizedResources: One of the basic uses of grid computing is to run an existing application on a different machine. The machine on which the application is normally run might be unusually busy due to a peak in activity. The job in question could be run on an idle machine elsewhere on the grid.  Parallel CPU capacity The potential for massive parallel CPU capacity is one of the most common visions and attractive features of a grid. In addition to pure scientific needs, such computing power is driving a new evolution in industries such as the bio-medical field, financial modeling, oil exploration, motion picture animation, and many others.  Virtual resources and virtual organizations for collaboration: Another capability enabled by grid computing is to provide an environment for collaboration among a wider audience. In the past, distributed computing promised this collaboration and achieved it to some extent.  Access to additional resources: As already stated, in addition to CPU and storage resources, a grid can provide access to other resources as well. The additional resources can be provided in additional numbers and/or capacity.  Resource balancing: grid federates a large number of resources contributed by individual machines into a large single-system image. For applications that are grid-enabled, the grid can offer a resource balancing effect by scheduling grid jobs on machines with low utilization.  Reliability: High-end conventional computing systems use expensive hardware to increase reliability. They are built using chips with redundant circuits that vote on results, and contain logic to achieve graceful recovery from an assortment of hardware failures.  Management: The goal to virtualized the resources on the grid and more uniformly handle heterogeneous systems will create new opportunities to better manage a larger, more distributed IT infrastructure. It will be easier to visualize capacity and utilization, making it easier for IT departments to control expenditures for computing resources over a larger organization 5