A Cloud Computing Scheduling and Its Evolutionary Approaches

Ahmed Subhi Abdalkafor, Alaa Abdalqahar Jihad, Emad Tariq Allawi

Abstract


Despite the increasing use of cloud computing technology because it offers unique features to serve its customers in a perfect way, exploiting the full potential is very difficult due to the many problems and challenges. Therefore, scheduling resources are one of these challenges. Researchers are still finding it difficult to determine which of the scheduling algorithms are appropriate and effective and that help increases the performance of the system to accomplish these tasks. This paper provides a broad and detailed survey of resource scheduling algorithms in the cloud computing environment and highlights the advantages and disadvantages of some algorithms to help researchers in selecting the best algorithms to schedule a particular workload to get a satisfy a quality of service, guarantee good utilization of the Cloud resources also minimizing the make-span.

Keywords


Cloud Computing; job Scheduling; Task scheduling; Load balancing

References


Isa . A.W.M , et al . Cloud computing adoption reference model, Indonesian Journal of Electrical Engineering and Computer Science, Vol. 16, No. 1, October 2019, pp. 395-400.

---------------------------------------

Olanrewaju, R. F., Islam, T., Khalifa, O. O., & Fajingbesi, F. E. (2018). Data in Transit Validation for Cloud Computing Using Cloud-Based Algorithm Detection of Injected Objects. Indonesian Journal of Electrical Engineering and Computer Science, 10(1), 348-353.I. Qian, L., Luo, Z., Du, Y., & Guo, L. (2009, December). Cloud computing: An overview. In IEEE International Conference on Cloud Computing (pp. 626-631). sSpringer, Berlin, Heidelberg.

-----------------------------------------------

https://www.statista.com/statistics/511283/worldwide-survey-cloud-computing-risks/

-----------------------------------

Chang, Ruay-Shiung, Chih-Yuan Lin, and Chun-Fu Lin. An adaptive scoring job scheduling algorithm for grid computing. Information Sciences 207 (2012): 79-89.

--------------------------------------------------------------

Zhou, Y., & Huang, X. (2013, November). Scheduling workflow in cloud computing based on ant colony optimization algorithm. In Business Intelligence and Financial Engineering (BIFE), 2013 Sixth International Conference on (pp. 57-61). IEEE.

-----------------------------------------------

Choudhary, A., Gupta, I., Singh, V., & Jana, P. K. (2018). A GSA based hybrid algorithm for bi-objective workflow scheduling in cloud computing. Future Generation Computer Systems.

-----------------------------------------------

GIBET TANI Hicham, EL AMRANI Chaker. Optimization of Task Scheduling Algorithms for Cloud Computing: A Review, SCAMS-SH'17, October 2017.

------------------------------------------

Athokpam Bikramjit Singh, Sathyendra Bhat J., Ragesh Raju, Rio D’Souza, A Comparative Study of Various Scheduling Algorithms in Cloud Computing, American Journal of Intelligent Systems, Vol. 7 No. 3, 2017, pp. 68-72.

---------------------------------------------------

S. Lakshmanan. A Survey on Heterogeneous Resource Scheduling Algorithm in Cloud Computing, IJSRSET, 2017.

--------------------------------------------------------------------------

Shameer A.P, Study on Different Scheduling Algorithm for Cloud Computing,International Journal of Advanced Research in Computer Science and Software Engineering, Volume 6, Issue 5, May 2016.

---------------------------------------------------------

M. Masdari, F. Salehi, M. Jalali, and M. Bidaki, A Survey of PSO-Based Scheduling Algorithms in Cloud Computing, J. Netw. Syst. Manag., vol. 25, no. 1, pp. 122–158, Jan. 2016.

----------------------------------------------------------------------

Maria A. Rodriguez and Rajkumar Buyya, A Taxonomy and Survey on Scheduling Algorithms for Scientific Workflows in IaaS Cloud Computing Environments, Concurrency and Computation: Practice and Experience (CCPE), Volume 29, No. 8, Pages: 1-23, ISSN: 1532-0626, Wiley Press, New York, USA, April 25, 2017.

--------------------------------------------------

Kamalpreet Kaur, Kanwalvir Singh Dhindsa. Comparative Study of Tools and Scheduling Algorithms of Cloud Computing, International Conference on Communication, Information and Computing Technology, 2015.

---------------------------------------------------------------

Simsy Xavier, S.P.Jeno Lovesum. A Survey of Various Workflow Scheduling Algorithms in Cloud Environment, International Journal of Scientific and Research Publications, 2013.

----------------------------------------------------------------------

Priya R. Lodha and Avinash P. Wadhe, Study of Different Types of Workflow Scheduling Algorithm in Cloud Computing. IJARCSEE Volume 2, Issue 4, aapril 2013.

-----------------------------------------------------

Kalka Dubey , Mohit Kumar . S.C. Sharma. Modified HEFT Algorithm for Task Scheduling in Cloud Environment, ELSEVIER, 2017.

-------------------------------------------------------

Ursa Sayeed, Arshad Shareef, T Sunil. An Optimal Task Scheduling Strategy in Cloud Computing Environment Utilizing FFA-PSO Algorithms, International Journal of Advance Research in Science & Engineering, 2017.

------------------------------------------------------------------

J. Kok Konjaang, Fahrul Hakim Ayob, Abdullah Muhammed. An Optimized Max-Min Scheduling Algorithm in Cloud Computing, Journal of Theoretical and Applied Information Technology, 2017.

-------------------------------------------------------------

Mehdi Sookhak, Abdullah Gani, Muhammad Khurram Khan, Rajkumar Buyya. Dynamic remote data auditing for securing big data storage in cloud computing. Information Scienses (2015).

--------------------------------------------------------

Arabi E. keshk, Ashraf B. El-Sisi, Medhat A. Tawfeek, Cloud Task Scheduling for Load Balancing based on Intelligent Strategy, I. J. Intelligent Systems and Applications, 2014, 05, 25 36 Published Online April 2014 in MECS.

----------------------------------------------------

Amit Agarwal, Saloni Jain, Efficient Optimal Algorithm of Task Scheduling in Cloud Computing Environment, International Journal of Computer Trends and Technology, Vol. 9, pp. 344-349, 2014.

-----------------------------------------------------------

Mohamed Abu Sharkh, Manar Jammal, Abdallah Shami, and Abdelkader Ouda, Resource Allocation in a Network-Based Cloud Computing Environment: Design Challenges, IEEE Communications Magazine. (November 2013).

--------------------------------------------------------

Chang, Ruay-Shiung, Chih-Yuan Lin, and Chun-Fu Lin. An adaptive scoring job scheduling algorithm for grid computing. Information Sciences 207 (2012): 79-89.

-----------------------------------------------------

Mizan, T. , Masud, S. M. R. A. , Latip, R. , Modified Bees Life Algorithm for Job Scheduling in Hybrid Cloud, International Journal of Engineering and Technology Volume 2 No. 6, June, 2012, 974-979.

----------------------------------------------------------------

Jiayin Li Meikang, Qiu Jianwei Niu, Wenzhong Gao, Ziliang Zong Xiao Qin, Feedback Dynamic Algorithms for Preemptable Job Scheduling in Cloud Systems, In the Proceeding of 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, pp.561-564, 2010.

--------------------------------------------------------------

Liu, S., Quan, G., & Ren, S. (2010, July). On-line scheduling of real-time services for cloud computing. In Services (SERVICES-1), 2010 6th World Congress on (pp. 459-464). IEEE.

---------------------------------------------------

Akilandeswari, P., & Srimathi, H. (2016). Survey and analysis on Task scheduling in Cloud environment. Indian Journal of Science and Technology, 9(37).‏

------------------------------------------------------------

Goel, H., & Chamoli, N. (2014). Job Scheduling Algorithms in Cloud Computing: A Survey. International Journal of Computer Applications, 95(23_.

-------------------------------------------

Athokpam Bikramjit Singh, Sathyendra Bhat J., Ragesh Raju, Rio D’Souza, A Comparative Study of Various Scheduling Algorithms in Cloud Computing, American Journal of Intelligent Systems, Vol. 7 No. 3, 2017, pp. 68-72.

----------------------------------------------------

Hamad, S. A., & Omara, F. A. (2016). Genetic-based task scheduling algorithm in cloud computing environment. International Journal of Advanced Computer Science and Applications, 7(4), 550-556.

----------------------------------------------------

Athokpam Bikramjit Singh, Sathyendra Bhat J., Ragesh Raju, Rio D’Souza, A Comparative Study of Various Scheduling Algorithms in Cloud Computing, American Journal of Intelligent Systems, Vol. 7 No. 3, 2017, pp. 68-72.

------------------------------------------------

Pandaba Pradhan, Prafulla Ku. Behera (2016), Modified Round Robin Algorithm for Resource Allocation in Cloud Computing, International Conference on Computational Modeling and Security, 1877-0509, Elsevier.

--------------------------------------------------------------

Rawshdeh, D. Zanoon (2015). STASR A New Task Scheduling Algorithm For Cloud Environment. Network Protocols and Algorithms, 7(2), 81-95.

EL AMRANI, C., & GIBET TANI, H. (2018). Smarter Round Robin Scheduling Algorithm for Cloud Computing and Big Data. Journal of Data Mining & Digital Humanities,7(2), 1943-3581.

----------------------------------------------------------------

Athokpam Bikramjit Singh, Sathyendra Bhat J., Ragesh Raju, Rio D’Souza, A Comparative Study of Various Scheduling Algorithms in Cloud Computing, American Journal of Intelligent Systems, Vol. 7 No. 3, 2017, pp. 68-72.

-----------------------------------------------------------------

Kaur, K., Kaur, N., & Kaur, K. (2018). A Novel Context and Load-Aware Family Genetic Algorithm Based Task Scheduling in Cloud Computing. In Data Engineering and Intelligent Computing (pp. 521-531). Springer, Singapore.

----------------------------------------------------------------------------

Pandaba Pradhan, Prafulla Ku. Behera (2016), Modified Round Robin Algorithm for Resource Allocation in Cloud Computing, International Conference on Computational Modeling and Security, 1877-0509, Elsevier.




DOI: http://doi.org/10.11591/ijeecs.v21.i1.pp%25p
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