Task Scheduling In Cloud Computing Based Deadline constraint
DOI:
https://doi.org/10.32792/jeps.v12i1.148Keywords:
Cloud Computing, task priority, scheduling algorithm, Virtual Machine, Genetic Algorithm (GA).Abstract
One of the newest technologies is cloud computing most aspects in distributed systems that are
most appealing . On-demand services are available on a pay-as-you-go system basis. In cloud computing,
Major research subjects include work scheduling and genetic algorithms. Task scheduling refers to the
process of allocating tasks to resources (virtual computers), while genetic algorithm is the process of
creating a community between resources in order to find optimal solutions to issues using the theory of
natural selection. We present a genetic approach to job scheduling with deadline constraints in this paper.
Each time the virtual machine load plus completion time is tested smaller and equal to the capacity of the
virtual machine and smaller and equal to the task deadline, two loops are formed, one for tasks and one
for virtual machines The suggested algorithm is compared to various algorithms Existing in use,
including as" An Effective Load Balancing Algorithm Based on Deadline Constraint) ELBAD( "and"
Elastic Load Balancer (ELB)" and the experimental results show that the proposed algorithm is superior
to others in terms of reducing rejected tasks and maximizing accepted tasks.
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References
(Aridah, Mohammed Ibrahim, 2016) “Task Scheduling Using Best-Level-Job-First on Private
Cloud Computing. ”A thesis Submitted in Partial Fulfillment of the Requirements for the Master
Degree in Computer Science Department of Computer Science Faculty of Information Technology
Middle East University August .
(Yuan, J. W. Ge and Y. S., 2013) "Research of cloud computing task scheduling algorithm based
on improved genetic algorithm," in Applied Mechanics and Materials , pp. 2426-2429.
(S. Ravichandran and D. E. Naganathan, 2013) "Dynamic Scheduling of Data Using Genetic
Algorithm in Cloud Computing," International Journal of Computing Algorithm, vol. 2, pp. 127-
.
(R. Kaur and S. Kinge, 2014)"Enhanced Genetic Algorithm based Task Scheduling in Cloud
Computing," International Journal of Computer Applications, vol. 101 .
(V. Vignesh, K. Sendhil Kumar, and N. Jaisankar, 2013)"Resource management and scheduling in
cloud environment," International Journal of Scientific and Research Publications, vol. 3, p. 1 .
(V. V. Kumar and S. Palaniswami, 2012)"A Dynamic Resource Allocation Method for Parallel
Data Processing in Cloud Computing," Journal of computer science, vol. 8, p. 780 .
(Z. Zheng, R. Wang, H. Zhong, and X. Zhang, 2011)"An approach for cloud resource scheduling
based on Parallel Genetic Algorithm," in Computer Research and Development (ICCRD), 2011 3rd
International Conference on, pp. 444-447.
(K. Thyagarajan, S. Vasu, and S. S. Harsha, 2013) , "A Model for an Optimal Approach for Job
Scheduling in Cloud Computing," in International Journal of Engineering Research and
Technology .
(S. Singh and M. Kalra, 2014)"Scheduling of Independent Tasks in Cloud Computing Using
Modified Genetic Algorithm," in Computational Intelligence and Communication Networks
(CICN), International Conference on, pp. 565-569.
(Khaldun Ibraheem Arif, 2020) “An Effective Load Balancing Algorithm Based on Deadline
Constraint Under Cloud Computing” , IOP Conf. Ser.: Mater. Sci. Eng. 928 032070.
(Mohit Kumar , Kalka Dubey , S.C.Sharma, 2017)“Elastic and flexible deadline constraint load
Balancing algorithm for cloud computing “ , ICSCC ,7-8 December 2017, Kurukshetra ,India.
(Salot, P., 2013) , "A survey of various scheduling algorithm in cloud computing environment,",
International Journal of Research and Engineering Technology (IJRET), Vol. 2(2), pp. 2319-1163.
(Goel, N.; and Garg, R. B, 2012)"A Comparative Study of CPU Scheduling Algorithms",
International Journal of Graphics and Image Processing, Vol. 2(4), pp. 245-251 .
(Shimpy, E., &Sidhu, M. J, 2014) “ Different Scheduling Algorithms In Different Cloud
Environment”. Algorithms, International Journal of Advanced Research in Computer and
Communication Engineering, 3(9),8003-8006.
(Kl Arif,AS Ketab)“Dynamic Time Quantum for an Efficient Round Robin in Cloud Computing”
,Journal of computational and Theoretical Nanoscience 16(5/6),2404-2409.
(Kaur, R., &Kinger, S, 2014) “ Analysis of Job Scheduling Algorithms in Cloud Computing”.
International Journal of Computer Trends and Technology (IJCTT),9(7), 379- 386.
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