Tasks Scheduling in Private Cloud Based on Levels of Users

Mohammed Fadhil

Abstract


In private cloud computing, tasks scheduling algorithms play a major role in the performance of the cloud system and the Quality of Services (QoS) that is provided to users. But, most current algorithms usually neglect the existence of different types / levels of users who working in the same institution. Tasks scheduling algorithm named Best-Level-Job-First (BLJF) has been proposed in this paper which takes into consideration the levels of users in the institution, in addition to the other commonly used parameters in scheduling tasks, when arranging the tasks of users in the queue for execution by the private cloud. The user level in the institution has been added as a new parameter to the set of parameters commonly used in the scheduling algorithms that are implemented by the private cloud providers. Performance tests showed that the BLJF algorithm succeeded in giving the QoS required for each user by distinguishing between them on the basis of levels of users.

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References


A. Ioannis, D. Helen, "Evaluation of gang scheduling performance and cost in a cloud computing system," The Journal of Supercomputing, vol. 59, no. 2, pp.975-992, 2010. doi:10.1007/s11227-010-0481-4

L. M. Mustafa, M. K. Elmahdy, M. H. Haggag, "Improve scheduling task based task Grouping in cloud computing system," International Journal of Computer Applications, vol. 93, no. 8, pp. 0975 – 8887, 2014. doi: 10.5120/16232-5561

R. Buyya, R. Ranjan, R. N. Calheiros, "Modeling and Simulation Of Scalable Cloud Computing Environments And The cloudsim toolkit: challenges and opportunities," High Performance Computing & Simulation HPCS'09, pp. 1-11, 2009. doi: 10.1109/HPCSIM.2009.5192685

R. N. Calheiros, R. Ranjan, A. Beloglazov, C. A. De Rose, R. Buyya, "Cloudsim: A toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms," Software: Practice and Experience, vol. 41 no. 1, pp. 23-50, 2011.‏ doi:10.1002/spe.995

S. Goyal, "Public vs private vs hybrid vs community - cloud computing: a critical review," I.J. Computer Network and Information Security, vol. 3, pp. 20-29, 2014. doi: 10.5815/ijcnis.2014.03.03

M. Katyal, A. Mishra, "A comparative study of load balancing algorithms in cloud computing environment," International Journal of Distributed and Cloud Computing, vol. 1, no. 2, 2013. (doi not available)

B. Rajkumar, S. Y. Chee, V. Srikumar, B. James, B. Ivona, "Cloud computing and emerging IT platforms: vision, hype, and reality for delivering computing as the 5th utility," Future Generation Computer Systems, vol. 25, pp. 599-616, 2009. doi=10.1.1.144.8397

K. Subramanian, Private clouds, Trend Micro Inc, 2011.

Navimipour, N. J., & Milani, F. S. "Task scheduling in the cloud computing based on the cuckoo search algorithm," International Journal of Modeling and Optimization, vol. 5, no. 1, 44, 2015. doi: 10.7763/IJMO.2015.V5.434

S. Lovesum, K. Krishnamoorthy, P. Prince, "An optimized QoS based cost effective resource scheduling in cloud," Journal of Theoretical & Applied Information Technology, vol. 66, no. 1, 2014. (doi not available)

E. Shimpy, Mr. J Sidhu. "Different scheduling algorithms in different cloud environment," International Journal of Advanced Research in Computer and Communication Engineering, vol. 3 no. 9, pp. 8003-8006, 2014. (doi not available)

M. A. F. Al-Husainy, "Best-Job-First CPU scheduling algorithm," Information Technology Journal, vol. 6, no. 2, pp. 288-293, 2007. doi: 10.3923/itj.2007.288.293

L. Yang, C. S. Panb, E. H. Zhanga, H.Y. Liua. "A new class of priority-based weighted fair scheduling algorithm," Physics Procedia, vol. 33, pp. 942–948, 2012. doi: 10.1016/j.phpro.2012.05.158

P. Shachee, S. Richa, "Double level priority based optimization algorithm for task scheduling in cloud computing," International Journal of Computer Applications, vol. 62, no. 20, pp. 33-37, 2013. doi: 10.5120/10213-5051

G. Shamsollah, M. Othman, "A priority based job scheduling algorithm in cloud computing," International Conference on Advances Science and Contemporary Engineering 2012 (ICASCE 2012). Procedia Engineering vol. 50. pp. 778–785, 2012. doi: 10.1016/j.proeng.2012.10.086

P. Swachil, B. Upendra, "Priority based job scheduling techniques in cloud computing: a systematic review," International Journal of Scientific & Technology Research, vol. 2, no. 11, 2013. (doi not available)

L. Guang, Chen-Yang, Daoguoli, "Scheduling research based on genetic algorithm and QoS constraints of cloud computing resources," Journal of Theoretical & Applied Information Technology, vol. 51, no. 1, 2013. (doi not available)

V. L. Atul, K. Y. Dharmendra, "Multi-objective tasks scheduling algorithm for cloud computing throughput optimization," International Conference on Intelligent Computing, Communication & Convergence (ICCC-2015). Procedia Computer Science vol. 48, pp. 107–113, 2015. doi: 10.1016/j.procs.2015.04.158

S. Selvarani, G. Sudha, "Improved cost-based algorithm for task scheduling in cloud computing," Proc. of the IEEE Int. Conf. on Computational Intelligence and Computing Research, ICCIC, pp. 1-5, 2010. doi: 10.1109/ICCIC.2010.5705847

A. Singh, S. Sahu, K. Gautam, M. Tiwari, "Private cloud scheduling with SJF, bound waiting, priority and load balancing," International Journal of Advanced Research in Computer Science and Software Engineering, vol. 4, no. 1, pp. 367-372, 2014. (doi not available)

X. Baomin, Z. Chunyan, H. Enzhao, H. Bin, "Job scheduling algorithm based on Berger model in cloud environment," Advances in Engineering Software vol. 42, pp. 419–425, 2011. doi: 10.1016/j.advengsoft.2011.03.007

K. Geetinder, K. Sarabjit, "Improved hyper-heuristic scheduling with load-balancing and RASA for cloud computing systems," International Journal of Grid and Distributed Computing, vol. 9, no. 1, pp.13-24, 2016. doi: 10.14257/ijgdc.2016.9.1.02

I. A. Mohammed, "Task scheduling using best-level-job-first on private cloud computing," M.Sc. thesis, Middle East University, 2016. (doi not available)


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