Relevant bibliographies by topics / Scheduling, data management, grid computing

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Scheduling, data management, grid computing'

Author: Grafiati
Published: 4 June 2021
Last updated: 12 February 2022

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Journal articles on the topic "Scheduling, data management, grid computing"

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Cao, Junwei, Stephen A. Jarvis, Subhash Saini, Darren J. Kerbyson, and Graham R. Nudd. "ARMS: An Agent-Based Resource Management System for Grid Computing." Scientific Programming 10, no. 2 (2002): 135–48. http://dx.doi.org/10.1155/2002/910792.

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Resource management is an important component of a grid computing infrastructure. The scalability and adaptability of such systems are two key challenges that must be addressed. In this work an agent-based resource management system, ARMS, is implemented for grid computing. ARMS utilises the performance prediction techniques of the PACE toolkit to provide quantitative data regarding the performance of complex applications running on a local grid resource. At the meta-level, a hierarchy of homogeneous agents are used to provide a scalable and adaptable abstraction of the system architecture. Ea
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Pei, Yun Xia, and Yue Zhang. "The Map-Reduce Parallelism Framework for Task Scheduling in Grid Computing." Advanced Materials Research 216 (March 2011): 111–15. http://dx.doi.org/10.4028/www.scientific.net/amr.216.111.

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As a rapid developing infrastructure, the grid can share widely distributed computing, storage, data and human resources. In order to improve the usability and QoS of the grid, the job management in the grid is very important, and becomes one of the key research issues in grid computing. Map-Reduce provide an efficient and easy-to-use framework for parallelizing the global optimization procedure. The simulation results show the usefulness and effectiveness of our task scheduling algorithm.
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Adamski, Marcin, Krzysztof Kurowski, Marek Mika, Wojciech Piątek, and Jan Węglarz. "Security Aspects in Resource Management Systems in Distributed Computing Environments." Foundations of Computing and Decision Sciences 42, no. 4 (2017): 299–313. http://dx.doi.org/10.1515/fcds-2017-0015.

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Abstract In many distributed computing systems, aspects related to security are getting more and more relevant. Security is ubiquitous and could not be treated as a separated problem or a challenge. In our opinion it should be considered in the context of resource management in distributed computing environments like Grids and Clouds, e.g. scheduled computations can be much delayed because of cyber-attacks, inefficient infrastructure or users valuable and sensitive data can be stolen even in the process of correct computation. To prevent such cases there is a need to introduce new evaluation m
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Pujiyanta, Ardi, Lukito Edi Nugroho, and Widyawan Widyawan. "Resource allocation model for grid computing environment." International Journal of Advances in Intelligent Informatics 6, no. 2 (2020): 185. http://dx.doi.org/10.26555/ijain.v6i2.496.

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Grid computing is a collection of heterogeneous resources that is highly dynamic and unpredictable. It is typically used for solving scientific or technical problems that require a large number of computer processing cycles or access to substantial amounts of data. Various resource allocation strategies have been used to make resource use more productive, with subsequent distributed environmental performance increases. The user sends a job by providing a predetermined time limit for running that job. Then, the scheduler gives priority to work according to the request and scheduling policy and
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Khorsheed, Murad B., Qasim M. Zainel, Oday A. Hassen, and Saad M. Darwish. "The Application of Fractal Transform and Entropy for Improving Fault Tolerance and Load Balancing in Grid Computing Environments." Entropy 22, no. 12 (2020): 1410. http://dx.doi.org/10.3390/e22121410.

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This paper applies the entropy-based fractal indexing scheme that enables the grid environment for fast indexing and querying. It addresses the issue of fault tolerance and load balancing-based fractal management to make computational grids more effective and reliable. A fractal dimension of a cloud of points gives an estimate of the intrinsic dimensionality of the data in that space. The main drawback of this technique is the long computing time. The main contribution of the suggested work is to investigate the effect of fractal transform by adding R-tree index structure-based entropy to exis
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Liu, Lin, Jian Guo, Jianyu Luo, Xiongfeng Xu, Kaiming Luo, and Shengming Wang. "Advance Evaluation of System Protection Control Strategy Based on Multi-scheme Concurrency." E3S Web of Conferences 252 (2021): 01038. http://dx.doi.org/10.1051/e3sconf/202125201038.

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According to rapid assessment requirement of system protection control strategy adaptability in future operation mode, combining with application status of distributed computing for power system security and stability analysis, based on design idea of asynchronism and concurrency, this paper proposes a multi-scheme concurrent computing framework suitable for coarse-grained case parallelism. By the way of multi-data section parallel, the asynchronous and concurrent scheduling management of computing task of multiple application functions under different sections is realized, which effectively i
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Ji, Xin, Da Hua Zhang, and De Yue Men. "Research on Heterogeneous Cloud Service Model for Smart Grid Business Application." Advanced Materials Research 860-863 (December 2013): 2427–33. http://dx.doi.org/10.4028/www.scientific.net/amr.860-863.2427.

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With the construction of smart grid and centralized data center, traditional information technology management mode already cannot meet the requirements on the timeliness and flexibility. Cloud computing technology can solve the complicated calculation, mass data processing, and network dynamic migration issues for electric power business, but when in the face of different business applications demand, due to the heterogeneous resources variety of applications bottleneck will be produced, difficult to achieve real "smart". In view of the smart grid application scenarios, heterogeneous resource
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Shahryari, Om-Kolsoom, Amjad Anvari-Moghaddam, and Shadi Shahryari. "Demand side management using the internet of energy based on LoRaWAN technology." Kurdistan Journal of Applied Research 2, no. 3 (2017): 112–19. http://dx.doi.org/10.24017/science.2017.3.35.

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The smart grid, as a communication network, allows numerous connected devices such as sensors, relays and actuators to interact and cooperate with each other. An Internet-based solution for electricity that provides bidirectional flow of information and power is internet of energy (IoE) which is an extension of smart grid concept. A large number of connected devices and the huge amount of data generated by IoE and issues related to data transmission, process and storage, force IoE to be integrated by cloud computing. Furthermore, in order to enhance the performance and reduce the volume of tra
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Gupta, Punit, and Deepika Agrawal. "Trusted Cloud Platform for Cloud Infrastructure." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 10, no. 8 (2013): 1884–91. http://dx.doi.org/10.24297/ijct.v10i8.1473.

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Reliability and trust Models are used to enhance secure , reliable scheduling , load balancing and QoS in cloud and Distributed environment. Trust models that are being used in Distributed and Grid environment, does not qualify cloud computing environment requirements. Since the parameters that have being taken into consideration in these trust models, does not fit in the cloud Infrastructure As A Service, a suitable trust model is proposed based on the existing model that is suitable for trust value management for the cloud IaaS parameters. Based on the above achieved trust values, trust bas
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SANDHOLM, THOMAS, PETER GARDFJÄLL, ERIK ELMROTH, OLLE MULMO, and LENNART JOHNSSON. "A SERVICE-ORIENTED APPROACH TO ENFORCE GRID RESOURCE ALLOCATIONS." International Journal of Cooperative Information Systems 15, no. 03 (2006): 439–59. http://dx.doi.org/10.1142/s0218843006001426.

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We present the SweGrid Accounting System (SGAS) — a decentralized and standards-based system for Grid resource allocation enforcement that has been developed with an emphasis on a uniform data model and easy integration into existing scheduling and workload management software. The system has been tested at the six high-performance computing centers comprising the SweGrid computational resource, and addresses the need for soft, real-time quota enforcement across the SweGrid clusters. The SGAS framework is based on state-of-the-art Web and Grid services technologies. The openness and ubiquity o
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Dissertations / Theses on the topic "Scheduling, data management, grid computing"

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Agarwalla, Bikash Kumar. "Resource management for data streaming applications." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/34836.

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This dissertation investigates novel middleware mechanisms for building streaming applications. Developing streaming applications is a challenging task because (i) they are continuous in nature; (ii) they require fusion of data coming from multiple sources to derive higher level information; (iii) they require
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Vernois, Antoine. "Ordonnancement et réplication de données bioinformatiques dans un contexte de grille de calcul." Lyon, École normale supérieure (sciences), 2006. http://www.theses.fr/2006ENSL0368.

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Au cours de cette thèse, nous nous sommes placés dans le contexte bien > particulier d'une catégorie d'applications bioinformatiques dont les > caractéristiques sont d'utiliser des banques de données de références en > lecture seule et d'avoir un coût en temps de calcul affine en la taille des > données. Une autre caractéristique concernant l'utilisation de ces > applications est que leur schéma d'utilisation reste constant dans le > temps. Dans ce cadre, nous avons défini un algorithme basé sur un programme > linéaire permettant de calculer un ordonnancement et un placeme
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Tordsson, Johan. "Portable Tools for Interoperable Grids : Modular Architectures and Software for Job and Workflow Management." Doctoral thesis, Umeå universitet, Institutionen för datavetenskap, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-19630.

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The emergence of Grid computing infrastructures enables researchers to shareresources and collaborate in more efficient ways than before, despite belongingto different organizations and being geographically distributed. While the Gridcomputing paradigm offers new opportunities, it also gives rise to newdifficulties. This thesis investigates methods, architectures, and algorithmsfor a range of topics in the area of Grid resource management. One studiedtopic is how to automate and improve resource selection, despite heterogeneityin Grid hardware, software, availability, ownership, and usage poli
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Smith, Andrew Cameron. "LHCb data management on the computing grid." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/3018.

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The LHCb detector is one of the four experiments being built to harness the proton-proton collisions provided by the Large Hadron Collider (LHC) at the European Organisation for Nuclear Research (CERN). The data rate expected, when the LHC experiments are fully operational, eclipses that of any previous scientific experiments and has motivated the adoption of a grid computing paradigm to store and process the data. Managing PetaBytes of data in a distributed environment provides a rich set of challenges related to scalability, reliability and performance. This thesis will present the data mana
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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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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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Delgado, Javier. "A grid computing network platform for enhanced data management and visualization." FIU Digital Commons, 2007. http://digitalcommons.fiu.edu/etd/2766.

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This thesis presents a novel approach towards providing a collaboration environment by using Grid Computing. The implementation includes the deployment of a cluster attached to a mural display for high performance computing and visualization and a Grid-infrastructure for sharing storage space across a wide area network and easing the remote use of the computing resources. A medical data processing application is implemented on the platform. The outcome is enhanced use of remote storage facilities and quick return time for computationally-intensive problems. The central issue of this thesis wor
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Brodard, Zacharie. "Workflow management and scheduling in a cloud computing context." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-249714.

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Public cloud providers have had a tremendous impact on the software engineering world recently by offering on-demand computing infrastructures and scalable managed solutions. The goal of this master degree project is to determine whether these services offered by public cloud providers can improve the design of workflow management and scheduling systems for data-driven workflows. A cloud based architecture for a distributed workflow management system was designed, implemented and experimented on. It allowed to confirm the value of cloud computing solutions to solve workflow scheduling problems
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Espling, Daniel. "Enabling Technologies for Management of Distributed Computing Infrastructures." Doctoral thesis, Umeå universitet, Institutionen för datavetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-80129.

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Computing infrastructures offer remote access to computing power that can be employed, e.g., to solve complex mathematical problems or to host computational services that need to be online and accessible at all times. From the perspective of the infrastructure provider, large amounts of distributed and often heterogeneous computer resources need to be united into a coherent platform that is then made accessible to and usable by potential users. Grid computing and cloud computing are two paradigms that can be used to form such unified computational infrastructures. Resources from several indepe
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Radwan, Ahmed M. "Information Integration in a Grid Environment Applications in the Bioinformatics Domain." Scholarly Repository, 2010. http://scholarlyrepository.miami.edu/oa_dissertations/509.

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Grid computing emerged as a framework for supporting complex operations over large datasets; it enables the harnessing of large numbers of processors working in parallel to solve computing problems that typically spread across various domains. We focus on the problems of data management in a grid/cloud environment. The broader context of designing a services oriented architecture (SOA) for information integration is studied, identifying the main components for realizing this architecture. The BioFederator is a web services-based data federation architecture for bioinformatics applications. Bas
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Books on the topic "Scheduling, data management, grid computing"

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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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Di Stefano, Michael. Distributed Data Management for Grid Computing. John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471738220.

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Di Stefano, Michael. Distributed Data Management for Grid Computing. John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471738220.

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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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Neelanarayanan, ed. Secure Data Management And Transaction of Heterogeneous Large Data Sets In Grid Computing Environment. Association of Scientists, Developers and Faculties, 2014.

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Grid and cloud database management. Springer, 2011.

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C, Leung Clement H., and Rahayu Johanna Wenny, eds. High performance parallel database processing and grid databases. J. Wiley, 2008.

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Min, Tjoa A., and SpringerLink (Online service), eds. Data Management in Grid and Peer-to-Peer Systems: Second International Conference, Globe 2009 Linz, Austria, September 1-2, 2009 Proceedings. Springer Berlin Heidelberg, 2009.

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Khadeer, Hussain Farookh, Morvan Franck, Tjoa A. Min, and SpringerLink (Online service), eds. Data Management in Cloud, Grid and P2P Systems: 5th International Conference, Globe 2012, Vienna, Austria, September 5-6, 2012. Proceedings. Springer Berlin Heidelberg, 2012.

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Book chapters on the topic "Scheduling, data management, grid computing"

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Hoschek, Wolfgang, Javier Jaen-Martinez, Asad Samar, Heinz Stockinger, and Kurt Stockinger. "Data Management in an International Data Grid Project." In Grid Computing — GRID 2000. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-44444-0_8.

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Ranganathan, Kavitha, and Ian Foster. "Computation Scheduling and Data Replication Algorithms for Data Grids." In Grid Resource Management. Springer US, 2004. http://dx.doi.org/10.1007/978-1-4615-0509-9_22.

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Nitzberg, Bill, Jennifer M. Schopf, and James Patton Jones. "PBS Pro: Grid Computing and Scheduling Attributes." In Grid Resource Management. Springer US, 2004. http://dx.doi.org/10.1007/978-1-4615-0509-9_13.

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Moreno, Rafael, and Ana B. Alonso-Conde. "Job Scheduling and Resource Management Techniques in Economic Grid Environments." In Grid Computing. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24689-3_4.

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Liu, Lilan, Tao Yu, Zhanbei Shi, and Minglun Fang. "Resource Management and Scheduling in Manufacturing Grid." In Grid and Cooperative Computing. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24680-0_18.

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Zheng, Ran, and Hai Jin. "An Integrated Management and Scheduling Scheme for Computational Grid." In Grid and Cooperative Computing. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24680-0_7.

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Giacomin, Pierpaolo, Alessandro Bassi, Frank J. Seinstra, and Thilo Kielmann. "Towards Coordinated Data Management For High-Performance Distributed Multimedia Content Analysis." In Grid Computing. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-09457-1_12.

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He, Xiaoshan, and Xian-He Sun. "Incorporating Data Movement into Grid Task Scheduling." In Grid and Cooperative Computing - GCC 2005. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11590354_49.

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Stockinger, Heinz, Omer F. Rana, Reagan Moore, and Andre Merzky. "Data Management for Grid Environments." In High-Performance Computing and Networking. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-48228-8_16.

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Yang, Shaofeng, Zeyad Ali, Houssain Kettani, Vinti Verma, and Qutaibah Malluhi. "Network Storage Management in Data Grid Environment." In Grid and Cooperative Computing. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24680-0_138.

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Conference papers on the topic "Scheduling, data management, grid computing"

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Wen Zhang, Junwei Cao, Yisheng Zhong, Lianchen Liu, and Cheng Wu. "An integrated resource management and scheduling system for grid data streaming applications." In 2008 9th IEEE/ACM International Conference on Grid Computing (GRID). IEEE, 2008. http://dx.doi.org/10.1109/grid.2008.4662807.

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Manfu Ma, Jian Wu, Shuyu Li, Dingjian Chen, and Zhengguo Hu. "A grid-distance based scheduling for grid resource management." In Eighth International Conference on High-Performance Computing in Asia-Pacific Region (HPCASIA'05). IEEE, 2005. http://dx.doi.org/10.1109/hpcasia.2005.4.

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Sha Fan. "Session Scheduling Algorithm of Grid Computing." In 2010 3rd International Conference on Knowledge Discovery and Data Mining (WKDD 2010). IEEE, 2010. http://dx.doi.org/10.1109/wkdd.2010.87.

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Liu, Feng, Weiwei Guo, and Xiaomin Zhao. "Network Resource Management and Scheduling in Grid Computing." In 2018 International Conference on Robots & Intelligent System (ICRIS). IEEE, 2018. http://dx.doi.org/10.1109/icris.2018.00061.

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"Issues Related to Scheduling in Grid computing." In International conference on Intelligent Systems, Data Mining and Information Technology. International Institute of Engineers, 2014. http://dx.doi.org/10.15242/iie.e0414074.

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Berral, Josep Ll, Ricard Gavalda, and Jordi Torres. "Adaptive Scheduling on Power-Aware Managed Data-Centers Using Machine Learning." In 2011 12th IEEE/ACM International Conference on Grid Computing (GRID). IEEE, 2011. http://dx.doi.org/10.1109/grid.2011.18.

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Ma, Ruyue, Xiangxu Meng, and Shijun Liu. "Data Management System in Manufacturing Grid." In 2006 IEEE International Conference on Services Computing (SCC'06). IEEE, 2006. http://dx.doi.org/10.1109/scc.2006.40.

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Xu, Meng, Lizhen Cui, Haiyang Wang, Yanbing Bi, and Ji Bian. "A Data-Intensive Workflow Scheduling Algorithm for Grid Computing." In 2009 Fourth ChinaGrid Annual Conference (ChinaGrid). IEEE, 2009. http://dx.doi.org/10.1109/chinagrid.2009.30.

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Lin, Chih-Kuang, Vladimir Zadorozhny, and Prashant Krishnamurthy. "Grid-Based Access Scheduling for Mobile Data Intensive Sensor Networks." In 2008 9th International Conference on Mobile Data Management (MDM). IEEE, 2008. http://dx.doi.org/10.1109/mdm.2008.36.

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Sato, Hitoshi, and Satoshi Matsuoka. "Data Management on Grid Filesystem for Data-Intensive Computing." In 2007 International Symposium on Applications and the Internet Workshops. IEEE, 2007. http://dx.doi.org/10.1109/saint-w.2007.38.

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