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Relevant bibliographies by topics / Grid computing (Computer system)

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Academic literature on the topic 'Grid computing (Computer system)'

Author: Grafiati

Published: 4 June 2021

Last updated: 7 February 2022

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Journal articles on the topic "Grid computing (Computer system)"

1

Budiharto, Widodo. "Implementasi dan Evaluasi Penerapan Globus Toolkit untuk Aplikasi Grid Computing." ComTech: Computer, Mathematics and Engineering Applications 3, no. 1 (2012): 695. http://dx.doi.org/10.21512/comtech.v3i1.2469.

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Grid computing is a distributed computing technology that utilizes resources connected through a free computer network, yet coordinated with a specific mechanism. The development of grid computing infrastructure is not easy because it takes skill and experience in the installation and configuration of both Linux-based and open source program. In this study, the author built a grid computing infrastructure based on Debian 4, and used Globus Toolkit 4.1.2 on three computers. The WSRF technology was tried to run as an indication that the grid infrastructure has been successfully built. Based on s

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Indrianingsih, Yuliani, Hero Wintolo, and Ika Kartika Sari. "PENERAPAN GRID COMPUTING UNTUK MENGKOMPILASI PROGRAM BERBAHASA C/C++." Conference SENATIK STT Adisutjipto Yogyakarta 1 (December 3, 2013): 67. http://dx.doi.org/10.28989/senatik.v1i0.41.

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Grid computing is a group of computers that connected to computer network and working together to complete a certain task. The computers inside must be coheren so the processors can work evenly when given a task from server. Grid computing can be used in many areas and purpopes, and in this research it will be used to compile C/C++ program. Compilation is a process to transform a human readable source code into a computer readable code. The compilation process will take place in a personal computer (PC). By using grid system in compilation process, the waiting time of a source code will be red

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Bry, François, Wolfgang E. Nagel, and Michael Schroeder. "Grid-Computing." Informatik-Spektrum 27, no. 6 (2004): 542–45. http://dx.doi.org/10.1007/s00287-004-0443-4.

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Demiya, Takehiko, Tomoki Yoshihisa, and Masanori Kanazawa. "Compact grid: a grid computing system using low resource compact computers." International Journal of Communication Networks and Distributed Systems 1, no. 2 (2008): 231. http://dx.doi.org/10.1504/ijcnds.2008.020263.

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Pinthong, Watthanai, Panya Muangruen, Prapat Suriyaphol, and Dumrong Mairiang. "A simple grid implementation with Berkeley Open Infrastructure for Network Computing using BLAST as a model." PeerJ 4 (July 28, 2016): e2248. http://dx.doi.org/10.7717/peerj.2248.

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Development of high-throughput technologies, such as Next-generation sequencing, allows thousands of experiments to be performed simultaneously while reducing resource requirement. Consequently, a massive amount of experiment data is now rapidly generated. Nevertheless, the data are not readily usable or meaningful until they are further analysed and interpreted. Due to the size of the data, a high performance computer (HPC) is required for the analysis and interpretation. However, the HPC is expensive and difficult to access. Other means were developed to allow researchers to acquire the powe

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Wu, Ming, and Xian-He Sun. "Grid harvest service: A performance system of grid computing." Journal of Parallel and Distributed Computing 66, no. 10 (2006): 1322–37. http://dx.doi.org/10.1016/j.jpdc.2006.05.008.

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PREVE, NIKOLAOS P., and EMMANUEL N. PROTONOTARIOS. "MONTE CARLO SIMULATION ON COMPUTATIONAL FINANCE FOR GRID COMPUTING." International Journal of Modeling, Simulation, and Scientific Computing 03, no. 03 (2012): 1250010. http://dx.doi.org/10.1142/s1793962312500109.

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Monte Carlo methods are a class of computational algorithms that rely on repeated random sampling to compute their results. Monte Carlo methods are often used in simulating complex systems. Because of their reliance on repeated computation of random or pseudo-random numbers, these methods are most suited to calculation by a computer and tend to be used when it is infeasible or impossible to compute an exact result with a deterministic algorithm. In finance, Monte Carlo simulation method is used to calculate the value of companies, to evaluate economic investments and financial derivatives. On

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Zhang, Jiaying, and Peter Honeyman. "A replicated file system for Grid computing." Concurrency and Computation: Practice and Experience 20, no. 9 (2008): 1113–30. http://dx.doi.org/10.1002/cpe.1286.

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Arnold, Dorian C., Henri Casanova, and Jack Dongarra. "Innovations of the NetSolve Grid Computing System." Concurrency and Computation: Practice and Experience 14, no. 13-15 (2002): 1457–79. http://dx.doi.org/10.1002/cpe.678.

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Liu, Li Jun. "Research on Computer Network Data Transfer Methods." Advanced Materials Research 926-930 (May 2014): 2807–10. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.2807.

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In order to spread across different locations, sharing of computer resources, and ease of use of idle CPU or storage space Resources, there is the concept of grid and grid computing. Data - intensive scientific and engineering applications ( such as seismic data Numerical Simulation of physics, computational mechanics, weather forecast ) needed in a wide area, quick and safe transmission in distributed computing environments Huge amounts of data. So how in a grid environment efficient, reliable, and secure transfer massive files are in the grid computing A study on the key issue. Design and re

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Dissertations / Theses on the topic "Grid computing (Computer system)"

1

Abraham, G. T. "Group-based parallel multi-scheduling methods for grid computing." Thesis, Coventry University, 2016. http://curve.coventry.ac.uk/open/items/9e286ae2-da74-42c9-978b-65d5eb3e3857/1.

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With the advent in multicore computers, the scheduling of Grid jobs can be made more effective if scaled to fully utilize the underlying hardware and parallelized to benefit from the exploitation of multicores. The fact that sequential algorithms do not scale with multicore systems nor benefit from parallelism remains a major challenge to scheduling in the Grid. As multicore systems become ever more pervasive in our computing lives, over reliance on such systems for passive parallelism does not offer the best option in harnessing the benefits of their multiprocessors for Grid scheduling. An ex

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Lorch, Markus. "PRIMA - Privilege Management and Authorization in Grid Computing Environments." Diss., Virginia Tech, 2004. http://hdl.handle.net/10919/26995.

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Computational grids and other heterogeneous, large-scale distributed systems require more powerful and more flexible authorization mechanisms to realize fine-grained access-control of resources. Computational grids are increasingly used for collaborative problem-solving and advanced science and engineering applications. Usage scenarios for advanced grids require support for small, dynamic working groups, direct delegation of access privileges among users, procedures for establishing trust relationships without requiring organizational level agreements, precise management by individuals of thei

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Killian, Rudi. "Dynamic superscalar grid for technical debt reduction." Thesis, Cape Peninsula University of Technology, 2018. http://hdl.handle.net/20.500.11838/2726.

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Thesis (MTech (Information Technology))--Cape Peninsula University of Technology, 2018.<br>Organizations and the private individual, look to technology advancements to increase their ability to make informed decisions. The motivation for technology adoption by entities sprouting from an innate need for value generation. The technology currently heralded as the future platform to facilitate value addition, is popularly termed cloud computing. The move to cloud computing however, may conceivably increase the obsolescence cycle for currently retained Information Technology (IT) assets. The term o

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Tang, Jia. "An agent-based peer-to-peer grid computing architecture." Access electronically, 2005. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20060508.151716/index.html.

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Buyya, Rajkumar 1970. "Economic-based distributed resource management and scheduling for grid computing." Monash University, School of Computer Science and Software Engineering, 2002. http://arrow.monash.edu.au/hdl/1959.1/8760.

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Muranganwa, Raymond. "Design and implementation of a multi-agent opportunistic grid computing platform." Thesis, University of Fort Hare, 2016. http://hdl.handle.net/10353/2722.

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Opportunistic Grid Computing involves joining idle computing resources in enterprises into a converged high performance commodity infrastructure. The research described in this dissertation investigates the viability of public resource computing in offering a plethora of possibilities through seamless access to shared compute and storage resources. The research proposes and conceptualizes the Multi-Agent Opportunistic Grid (MAOG) solution in an Information and Communication Technologies for Development (ICT4D) initiative to address some limitations prevalent in traditional distributed system i

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Bsoul, Mohammad. "Economic scheduling in Grid computing using Tender models." Thesis, Loughborough University, 2007. https://dspace.lboro.ac.uk/2134/3094.

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Economic scheduling needs to be considered for Grid computing environment, because it gives an incentive for resource providers to supply their resources. Moreover, it enforces efficient use of resources, because the users have to pay for their use. Tendering is a suitable model for Grid scheduling because users start the negotiations for finding suitable resources for executing their jobs. Furthermore, the users specify their job requirements with their requests and therefore the resources reply with bids that are based on the cost of taking on the job and the availability of their processors

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Al, Bodour R. "A flexible model supporting QoS and reallocation for grid applications." Thesis, Coventry University, 2011. http://curve.coventry.ac.uk/open/items/208265d9-ee5d-4c88-a955-466c9fc3dfa3/1.

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The rise of business-oriented and commercial applications for Grid computing environments has recently gathered pace. Grid computing traditionally has been linked with scientific environments, where heterogeneous resources provided by Grid systems and infrastructures were employed for carrying out computationally-intensive and data-intensive scientific experiments or applications that may have not been possible before. The natural progression is that business-oriented applications will look to build on this success and utilise the large number of heterogeneous Grid resources including computat

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Yang, Cheng. "Development of Intelligent Energy Management System Using Natural Computing." University of Toledo / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1341375203.

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Sandholm, Thomas. "Managing Service Levels in Grid Computing Systems : Quota Policy and Computational Market Approaches." Licentiate thesis, KTH, Numerical Analysis and Computer Science, NADA, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4346.

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<p>We study techniques to enforce and provision differentiated service levels in <i>Computational Grid</i> systems. The Grid offers simplified provisioning of peak-capacity for applications with computational requirements beyond local machines and clusters, by sharing resources across organizational boundaries. Current systems have focussed on access control, i.e., managing who is allowed to run applications on remote sites. Very little work has been done on providing differentiated service levels for those applications that are admitted. This leads to a number of problems when scheduling jobs

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Books on the topic "Grid computing (Computer system)"

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Craig, Fellenstein, ed. Grid computing. Prentice Hall Professional Technical Reference, 2004.

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Grid computing security. Springer, 2007.

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Desktop grid computing. Taylor & Francis, 2012.

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Eric, Yen, and SpringerLink (Online service), eds. Grid Computing: International Symposium on Grid Computing (ISGC 2007). Springer US, 2009.

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Grid computing for developers. Charles River Media, 2005.

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Chakrabarti, Anirban. Grid computing security. Springer, 2010.

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Richard, Wellner, ed. Grid computing: The savvy manager's guide. Elsevier/Morgan Kaufmann, 2005.

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International Business Machines Corporation. International Technical Support Organization, ed. Introduction to grid computing with Globus. 2nd ed. IBM Corporation, International Technical Support Organization, 2003.

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9

Distributed data management for grid computing. John Wiley, 2005.

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Stefano, Michael Di. Distributed Data Management for Grid Computing. John Wiley & Sons, Ltd., 2005.

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Book chapters on the topic "Grid computing (Computer system)"

1

Higuchi, Kenji, Toshiyuki Imamura, Yoshio Suzuki, et al. "Grid Computing Supporting System on ITBL Project." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39707-6_19.

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Xu, Zhiwei. "Vega Grid: A Computer Systems Approach to Grid Research." In Grid and Cooperative Computing. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24679-4_1.

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Xu, Zhiwei, and Wei Li. "Vega Grid: A Computer Systems Approach to Grid Research." In Grid and Cooperative Computing. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24679-4_90.

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Lai, Woodas W. K., Kam-Wing Ng, and Michael R. Lyu. "Integrating Trust in Grid Computing Systems." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30208-7_130.

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Kang, KyungWoo, and Gyun Woo. "A Resource Selection Scheme for Grid Computing System META." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30208-7_138.

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Zhang, Yang, Jiannong Cao, Sanglu Lu, Baoliu Ye, and Li Xie. "A QoS-Enabled Services System Framework for Grid Computing." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30208-7_8.

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Sarangi, Anuraag, Alok Shriram, and Avinash Shankar. "A Scheduling Model for Grid Computing Systems." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45644-9_11.

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Qing-Kui, Chen, and Wei Wang. "Cooperative Communication System for Parallel Computing Agents in Multi-cluster Grid." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-88140-7_20.

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Yahaya, Bakri, Rohaya Latip, Mohamed Othman, and Azizol Abdullah. "Dynamic Load Balancing Policy in Grid Computing with Multi-Agent System Integration." In Software Engineering and Computer Systems. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22170-5_36.

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Lim, Changsun, Seongjin Ahn, and Jinwook Chung. "A Study on Computing Resource Partition for Increasing Efficiency of Grid System." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02556-3_63.

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Conference papers on the topic "Grid computing (Computer system)"

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Shuai Zhang, Xuebin Chen, Shufen Zhang, and Xiuzhen Huo. "The comparison between cloud computing and grid computing." In 2010 International Conference on Computer Application and System Modeling (ICCASM 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccasm.2010.5623257.

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Shen, Zhi-Dong, Fei Yan, Wei-Zhong Qiang, Xiao-Ping Wu, and Huan-Guo Zhang. "Grid System Integrated with Trusted Computing Platform." In 2006 International Multi-Symposiums on Computer and Computational Sciences (IMSCCS). IEEE, 2006. http://dx.doi.org/10.1109/imsccs.2006.72.

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Lee, Liang-teh, Chin-hsiian Liang, and Hung-yuan Chang. "An Adaptive Task Scheduling System for Grid Computing." In The Sixth IEEE International Conference on Computer and Information Technology. IEEE, 2006. http://dx.doi.org/10.1109/cit.2006.36.

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M., Maithili. "Grid Computing in Mathematical Expression." In International Conference on Computer Applications — Database Systems. Research Publishing Services, 2010. http://dx.doi.org/10.3850/978-981-08-7300-4_1576.

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Shouming, Ma, Yu Chunlei, and Gu Wei. "Towards Cloud Computing Security Considerations in Smart Grid." In 3rd International Conference on Computer Science and Service System. Atlantis Press, 2014. http://dx.doi.org/10.2991/csss-14.2014.104.

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Huang Hai-sheng and Wang Ru-chuan. "A new subjective trust model in grid computing." In 2010 International Conference on Computer Application and System Modeling (ICCASM 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccasm.2010.5623016.

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Amato, A., M. Calabrese, V. Di Lecce, and V. Piuri. "Dynamic Simulation for Grid Computing Systems." In 2006 IEEE Conference on Virtual Environments, Human-Computer Interfaces and Measurement Systems. IEEE, 2006. http://dx.doi.org/10.1109/vecims.2006.250792.

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Demiya, Takehiko, Tomoki Yoshihisa, and Masanori Kanazawa. "A Grid Computing System using Low Resource Compact Computers." In 2007 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing. IEEE, 2007. http://dx.doi.org/10.1109/pacrim.2007.4313197.

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Liu, Guohua. "USI-Uniform Secure Interoperation in Grid Service and Computing System." In 2010 2nd International Conference on Information Engineering and Computer Science (ICIECS). IEEE, 2010. http://dx.doi.org/10.1109/iciecs.2010.5678194.

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Tangmankhong, Thagorn, Peerapon Siripongwutikorn, and Tiranee Achalakul. "Peer-to-peer fault tolerance framework for a grid computing system." In 2012 International Joint Conference on Computer Science and Software Engineering (JCSSE). IEEE, 2012. http://dx.doi.org/10.1109/jcsse.2012.6261983.

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Reports on the topic "Grid computing (Computer system)"

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Rana, Abhishek S. A Globally Distributed Grid Monitoring System to Facilitate High-Performance Computing at D0/SAM-Grid. Office of Scientific and Technical Information (OSTI), 2002. http://dx.doi.org/10.2172/1421666.

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