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An Efficient Heuristics Scheduling Algorithm for Cloud Computing
Abstract
In modern world Cloud Computing is one of the most promising and evolving areas of computer science. In the present scenario, cloud computing covers almost entire internet based activity. It brings a revolution in Information Technology industry by ordering on-demand of resources. Cloud is developing day by day and faces many challenges, one of them is scheduling. Scheduling in cloud is responsible for selection of best suitable resources for task execution, by taking some parameters into consideration. Schedulers for cloud computing determine on which processing resource jobs of a workflow should be allocated. This article introduces the scheduling problem in hybrid clouds presenting the main characteristics to be considered when scheduling workflows, as well as a brief survey of some of the scheduling algorithms used in these systems.
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References
. M. Dikaiakos et al., “Cloud Computing: Distributed Internet Computing for IT and Scientific Research,” IEEE Internet Computing, vol. 13, no. 5, Sept.–Oct. 2009, 10–13.
. M. Batista and N. L. S. da Fonseca, “A Survey of Self-Adaptive Grids,” IEEE Commun. Mag., vol. 48, no. 7, July 2010, pp. 94 100.
. Y. Gil, E. Deelman et al., “Examining the Challenges of Scientific Workflows,” IEEE Computer, vol. 40, no. 12, Dec. 2007, pp. 24–32.
. Deelman et al., “Griphyn and Ligo, Building A Virtual Data Grid for Gravitational Wave Scientists,” 11th IEEE Int’l. Symp. High Perf. Distrib. Computing, 2002, pp. 225–34.
. L. F. Bittencourt and E. R. M. Madeira, “HCOC: A Cost Optimization Algorithm for Workflow Scheduling in Hybrid Clouds,” J. Internet Svcs. and Apps., vol. 2, no. 3, Dec 2011, pp. 207–27.
. T. A. L. Genez, L. F. Bittencourt, and E. R. M. Madeira, “Workflow Scheduling for SaaS/PaaS Cloud Providers Considering Two SLA Levels,” IEEE/IFIP NOMS, Apr. 2012.
. Topcuoglu, S. Hariri, and M.-Y. Wu, “Performance-Effective and Low-Complexity Task Scheduling for Het-erogeneous Computing,” IEEE Trans. Parallel and Distrib. Sys. vol. 13, no. 3, 2002, pp. 260–74.
. J. Yu, R. Buyya, and C. K. Tham, “Cost-based Scheduling of Scientific Workflow Applications on Utility Grids,”
. Int’l. Conf. e-Science and Grid Computing, July 2005, 140–47.
. S. Abrishami, M. Naghibzadeh, and D. Epema, “Cost-Driven Scheduling of Grid Workflows Using Partial Criti-cal Paths,” 11th IEEE/ACM GRID, Oct. 2010, pp. 81–88.
. S. Pandey et al., “A Particle Swarm Optimization-Based Heuristic for Scheduling Workflow Applications in Cloud Computing Environments,” 24th IEEE AINA, Apr. 2010, pp. 400–07.
. Z. Wu et al., “A Revised Discrete Particle Swarm Opti-mization for Cloud Workflow Scheduling,” Int’l. Conf. Computational Intelligence and Security, Dec. 2010, pp. 184–88.
. Christina Delimitrou and Christos Kozyrakis, “Paragon: QoS-Aware Scheduling for Heterogeneous Datacenters”, In Proc. of the Eighteenth International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), Houston, March 2013.
. Jing Liu, Xing-Guo Luo, Xing-Ming Zhang, Fan Zhang and Bai-Nan Li, “Job Scheduling Model for Cloud Computing Based on Multi-Objective Genetic Algorithm”, International Journal of Computer Science Issues, Vol. 10, Issue 1, No 3, January 2013.
. Santana-Perez, I., Ontology Eng. Group, Univ. Politec. de Madrid, Madrid, Spain, Perez-Hernandez, M.S. , “A semantic scheduler architecture for federated hybrid clouds”, Cloud Computing (CLOUD), IEEE 5th International Conference on 2012.
. S. Abrishami, M. Naghibzadeh, “Deadline-Constrained Workflow Scheduling in Software as a Service Cloud”, Scientia Iranica, Volume 19, Issue 3, June 2012.
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