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GRID COMPUTING. Asad Khailany , Eastern Michigan University Wafa Khorsheed , Eastern Michigan University. ABSTRACT. More computing power needed to do what we want to do in the biological, chemical, medical, educational, industrial, and business fields .
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GRID COMPUTING Asad Khailany , Eastern Michigan University Wafa Khorsheed , Eastern Michigan University
ABSTRACT More computing power needed to do what we want to do in the biological, chemical, medical, educational, industrial, and business fields . There is need for much more computing power to study and understand the universe. Can distributed computing processing management become more efficient, more secure and more economically feasible? Grid computing is a new paradigm for next-generation computing to provide ways to make very large large computing power available worldwide to whoever needed either free or for an economically feasible price. The driving idea behind grid computing is harnessing unused CPU power to perform compute-intensive applications.
Introduction • in spite of the tremendous impressive, and unthinkable improvements of hardware, and software systems we still do not have enough computing efficiency in terms of speed, storage to perform many ambitious projects such as searching for extraterrestrial life, discovering universe more efficiently, and solving large science, commerce, and engineering problems efficiently, and more economically. • Perhaps the only way to get such extremely large efficient computing power and storage capacity is to develop biological computers where the brains of the beings along with DNA technology to be employed for creating massive parallel distributing computing systems with massive flexible and cheap storage media. • However currently biological computing technology is in its infancy, and that is a dream it may be realized in the next century. • Since the mid 1990s many researchers have been thinking about providing computing in a grid style like electricity where electricity to be provided to places were needed and no power to be wasted, and each supplier of the electricity power has its own manager to decide on allocation policies, customer relationship and terms of supplying power
INTRODUCTION _Continued • Protocols and strategies must be developed to control resources, to provide security, to satisfy users demands and to insure the delivery of needed computing power at economically feasible price. • The idea of grid computing is to create a virtual super parallel distributed computing system by using the computational power of idle PCs on the Internet or networks • the world largest distrusted computing system, and the most well known grid computing implementations is SETI@home (Search for Extraterrestrial Intelligence) of University of California at the Berkeley campus. SETI@home grid computing is designed to harness the power of the idle Internet connected PCs allover the world to form a virtual super computer.
Definition of Grid Computing • professor Ian Foster of University of Chicago, and a director of Globus Project of Argonne National laboratory proposed following checklist for aggregation of computers to become a grid computing. • A computing system that coordinates resources which are not subject to centralized control. • The system has to use standard, open, general-purpose protocols and interfaces. • The system should deliver quality services.
Definition of Grid Computing Rajkumar Buyya [3] in his just released PhD thesis on "Grid Economy : Resource Management and Scheduling" identified the four main characteristics of a grid system to be: • Multiple Administrative Domains and Autonomy. Grid computational resources owned by different organizations, the autonomy and the private managerial authorities must be honored. • Heterogeneity. A Grid involves a multiple heterogeneous resources with many different technologies and computer operating systems • Scalability: Number of resources on a Grid may increase very rapidly, and such rapid increment of resources may degrade the performance of the system. Therefore applications that require vast number of resources in different geographical locations must be latency and bandwidth tolerant. • Dynamistic or Adoptability. Resource managers must always be ready to reassign a task, which was assigned to a computing resource when such a resource fails to perform a task. Because of the vast number of resources in a Grid the probability of some resources to fail is very high
Definition of Grid Computing IBM in its IBM Grid Computing website provided a similar definition for a grid as a virtual dynamic system to be formed from a collection of computing resources of local or wide area networks to provide unlimited access, power and collaboration to everyone connected to grid through secure coordinate resource sharing.
Definition of Grid Computing Grid computing can be defined to be a methodology to provide the users a virtual supper computer by forming an infrastructure of software, and hardware through clustering technique utilizing databases, networks, scientific instruments, computing methodologies and software packages from many different resources, and locations where the user can work collaboratively.
Differences between Grid clustering and ordinary clustering • In grid computing each computer (node) has its own manager, and its own allocation policy, and strategy. • In ordinary clustering there is a centralized management to schedule tasks, and to allocate resources to different nodes, and all nodes work cooperatively toward a common goal defined by the central manager
Issues Concern the development of Grid computing • Application development tools needed for grids. • Polices for sharing resources. • Security issues (authentication, privacy, integrity) . • Resource management issues(quality of services, resource allocation, resource trading). • Scheduling (scheduling strategies, resource discovery, negotiation, resource selection, access cost quality of services). The Globus Toolkit , developed by Argonne National Laboratory and the University of Southern California addresses many of the above issues. Rajkumar Buyya devoted his Ph. D. dissertation to resource management and scheduling in Grid computing
Types of Grid Computing • One type of grid computing arrangement is a local cluster, where one main grid server on a single very-high-speed network handles one task allows some special users permits to manage the task and other users granted privileges to review and inspect intermediate and final results. • Another type of grids is the grid campus which involves many grid servers and many tasks. • The third type global network grid permits the usage of computing resources on the web and even on the private networks. See Cutise Frankin [10].
HOW IT WORKS? • In grid computing environment there is a central computing server which maintains the control of all processes • The central processor divides a task into subtasks (processes), and finds computational resources, which agree to accept the processes and perform the assigned tasks . • Each of these computational resources have their own manager and their own policies to accept or not to accept a task and at what cost if any. • Each of these computational resources may be a server, which may distribute the tasks received from the central server toother servers, and to other computational resources. • All computing resources and servers have their own policies and their own independent managers . • The central server and other servers try to assign works to computers with surplus processing power on the grid
HOW IT WORKS? • Any failed task assigned to any computing resources is reassigned to other computing nodes, which agree to accept the task • A grid is a dynamic hierarchicalstructure of many servers where all processing for a subtask occurs on a single network. • The controlling cluster server assembles the results of completed subtasks and assigns the next subtask to next available and agreeable computing resource until the whole task is completed. • The completed results that were assembled by a server are forwarded to the upper hierarchy level, which asked for service to be done.
Benefits Of Grid Computing: • Many scientific, business, research, economical, educational and other problems which previously were unsolvable may become solvable by having unlimited power and access through grid to vast amount of information and computer processing power from many heterogeneous, different geographical locations, and instruments • Through collaboration among many different organizations and individuals common problems can be handled more effectively, more easily, and solved more economically. • Through sharing hardware and software resources the total cost of processing, and storage of information will be decreased.
SCIENTFIC, AND COMMERCIAL USE OF GRID COMPUTING • The interest of Grid Computing has not and is not limited only to the scientific, and educational environment. • iIs usages have been adopted by many business, commerce, manufacturing, health, and government organizations. • Early corporate adopted Grid computing were Bioinformatics, oil and gas exploration, automotive and aerospace engineering, financial services, and drug manufacturing companies. • Bristol_Myers USA TODAY issue of January 8 2003 saved millions of Dollars by sharing PCs to run programs when they are idle.
Commercial Companies & Grids • Many commercial companies have created business Grid applications products based on the Open Grid Services Architecture(OGSA),standards developed by theGlobal Grid Foru . Some of companies producing such type products are: • Avaki [11] • Datasynapse [12] • ENTROPIA [13] • PLATFORM [14] . • Sun(developed grid initiative based on their own hardware). • IBM(developed grid initiative based on their own hardware). • Hewlett-Packard(developed grid initiative based on their own hardware).
CONCLUSION Grid computing, started from universities and research institutes. Its advantage was immediately recognized and research institutes, business, industrial, commerce, health, governments and other organizations have rapidly adopted the technology. Grid technology is not yet perfect but in a very near future many more effective grid tools will be improved and become available. Through Grid computing any organization small or large or individuals will have access to a virtual super computing power, huge banks of databases, and almost unlimited storage space.
REFERENCES 1.Grid Computing ComputerWorld: http://computerworld.com/networkingtopics/networking/management/story/0,10801,76946,00.html 2. Globus Project: http://www-unix.mcs.anl.gov/metaneos/talks/foster-html/ 3. Rajkumar Buyya: http://www.gridcomputing.com/ 4. RajKumar Buyya Ph. D. dissertation: http://www.cs.mu.oz.au/~raj/thesis/ 5. http://www.cs.mu.oz.au/ 6. http://www.unimelb.edu.au/ 7.IBM Grid Computing: http://www-1.ibm.com/grid/ 8.USA-TODAY:http://www.usatoday.com/money/industries/technology/2003-01-08-shared-computing_x.htm 9. Global Grid Forum Over view: http://www.gridforum.org/ 10. Curtise Franklin Jr. Network World Fusion 01/6/3: http://www.nwfusion.com/research/2003/0106grid.html 11. Avaki: http://www.avaki.com/ 12. Datasynapse http://www.datasynapse.com/ 13. ENROPIA: http://www.entropia.com/ 14. Platform: http://www.platform.com/