A Review on Task Model and Task Scheduling in Cloud Computing

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2017 by IJETT Journal
Volume-48 Number-2
Year of Publication : 2017
Authors : Sandeep kaur, Pooja Nagpal
DOI :  10.14445/22315381/IJETT-V48P216


Sandeep kaur, Pooja Nagpal "A Review on Task Model and Task Scheduling in Cloud Computing", International Journal of Engineering Trends and Technology (IJETT), V48(2),88-93 June 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Cloud computing is an emerging technology, that based upon internet computing and share resources (software and hardware) depends upon their demand. Cloud computing works on its important feature known as virtualization in order to access remote and geographically distributed resources. Depending upon cloud service provider and user requirements, a number of virtual machines are used. So it is necessary to schedule VM request. Nowadays scheduling task becomesa challenge for researchers. So a number of algorithms are used to provide proficiency of task and resource scheduling. In this paper, we have discussed different scheduling algorithms along with task model known as DAG (Directed Acyclic graph).


1. Chauhan N. and Saxena A. (2013), “A Green Software Development Lifecycle for Cloud Computing”, IEEE’s IT Pro, pp. 28-34.
2. Kaur, Rajwinder, and Pawan Luthra, “Load balancing in cloud computing,” Second Symposium on Cloud computing. 2012.
3. Xiao, Zhen, Weijia Song, and Qi Chen, “Dynamic resource allocation using virtual machines for cloud computing environment,” IEEE transactions on parallel and distributed systems 24.6 (2013): 1107-1117.
4. D. Kliazovich, J. E. Pecero, A. Tchernykh, P. Bouvry, S. U. Khan and A. Y. Zomaya, “CA-DAG: Communication-Aware Directed Acyclic Graphs for Modeling Cloud Computing Applications,” 2013 IEEE Sixth International Conference on Cloud Computing, Santa Clara, CA, 2013, pp. 277-284.
5. X. J. Xu, C. B. Xiao, G. Z. Tian and T. Sun, “Hybrid Scheduling Deadline-Constrained Multi-DAGs Based on Reverse HEFT,” 2016 International Conference on Information System and Artificial Intelligence (ISAI), Hong Kong, 2016, pp. 196-202.
6. Selvarani, S., and G. Sudha Sadhasivam, “Improved cost-based algorithm for task scheduling in cloud computing,” Computational intelligence and computing research (iccic), 2010 ieee international conference on. IEEE, 2010.
7. Z. Liu, T. Qin, W. Qu and W. Liu, “DAG Cluster Scheduling Algorithm for Grid Computing,” 2011 14th IEEE International Conference on Computational Science and Engineering, Dalian, Liaoning, 2011, pp. 632-636.
8. L. F. Bittencourt, R. Sakellariou and E. R. M. Madeira, “DAG Scheduling Using a Lookahead Variant of the Heterogeneous Earliest Finish Time Algorithm,”2010 18th Euromicro Conference on Parallel, Distributed and Network-based Processing, Pisa, 2010, pp. 27-34.
9. Patil, Neeta, and Deepak Aeloor, “A review-different scheduling algorithms in cloud computing environment,” Intelligent Systems and Control (ISCO), 2017 11th International Conference on. IEEE, 2017.
10. Kavyasri, M. N., and B. Ramesh, “Comparative study of scheduling algorithms to enhance the performance of virtual machines in cloud computing,”Emerging Trends in Engineering, Technology and Science (ICETETS), International Conference on. IEEE, 2016.
11. K. R. Shetti, S. A. Fahmy and T. Bretschneider, “Optimization of the HEFT Algorithm for a CPU-GPU Environment,”2013 International Conference on Parallel and Distributed Computing, Applications and Technologies, Taipei, 2013, pp. 212-218.
12. Abdelkader, Doaa M., and Fatma Omara, “Dynamic task scheduling algorithm with load balancing for heterogeneous computing system,” Egyptian Informatics Journal 13.2 (2012): 135-145.

Cloud computing, scheduling, DAG, HEFT.