International Journal of Scientific & Technology Research

Home About Us Scope Editorial Board Blog/Latest News Contact Us
10th percentile
Powered by  Scopus
Scopus coverage:
Nov 2018 to May 2020


IJSTR >> Volume 9 - Issue 1, January 2020 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

A Survey On Various Types Of Task Scheduling Algorithm In Cloud Computing Environment

[Full Text]



Priyanka Sharma , Dr. Sanjay Shilakari, Uday Chourasia, Priyanka Dixit, Alpana Pandey





Now a days, Cloud computing has become an significant and most popular computing model that usually supports on demand services. Cloud Computing provides its services on pay-as-you-go basis .By using cloud computing resources expeditiously and by reducing in managing time and cost and increasing the outcome of the project is the main idea of cloud service provider. Therefore, using effective cloud scheduling algorithms is still main concern in cloud computing. Task scheduling is a pivotal part in the field of the cloud environment. In task scheduling user requests for certain task, then tasks are scheduled to certain resources at a specific exemplification of time. Basically task scheduling mainly focuses to diminish the make span and lengthen the resource utilization. Task scheduling is an Non Polynomial-Complete problem. There are lots of subsisting trail-and-error techniques for task scheduling till now but more amelioration and rectification is needed for better execution and to increase the efficiency of task scheduling till now, there is no combined study of task scheduling mechanism in cloud computing which describes its parameter, pros, cons, algorithm. This paper mainly emphasis on explaining Comparison on different Task scheduling algorithm in cloud computing adaptive



[1] Maheswari. R and S. Selvi. “A Survey on Scheduling Algorithms in Cloud Computing”, International Journal of Engineering Research & Technology (IJERT), Vol. 2 Issue 10, ISSN: 2278-0181, October – 2013.
[2] Fei Teng. “Resource allocation and scheduling models for cloud computing”, Paris, 2011.
[3] Emeakaroha, V.C., Brandic, I., Maurer, M. and Breskovic, I.. “SLA-Aware Application Deployment and Resource Allocation in Clouds”, IEEE, 2011.
[4] Daniel, D., Lovesum, S.P.J., “A novel approach for scheduling service request in cloud with trust monitor”, IEEE, 2011.
[5] Boloor, K., Chirkova, R., Salo, T., Viniotis, Y., "Heuristic-Based Request Scheduling Subject to a Percentile Response Time SLA in a Distributed Cloud", IEEE, 2011.
[6] Mehdi, N.A., Mamat, A. Amer, A., Abdul-Mehdi, Z.T., "Minimum Completion Time for Power-Aware a. Scheduling in Cloud Computing", IEEE, 2012.

[7] Luna Mingyi Zhang, Keqin Li, Yan-Qing Zhang, "Green Task Scheduling Algorithms with Speeds Optimization on Heterogeneous Cloud Servers", IEEE, 2011
[8] Xin Lu, Zilong GU, “A load-adaptive cloud resource scheduling model based on ant colony algorithm”, IEEE, 2011.
[9] Gao Ming and Hao Li, "An Improved Algorithm Based on Max-Min for Cloud Task Scheduling", Yunnam University, China, 2011.
[10] Ching-Hsien Hsu, Tai-Lung Chen, "Adaptive Scheduling Based on Quality of Service in Heterogeneous Environments", IEEE, 2010.
[11] Shuo Liu, Gang Quan, Shangping Ren, "On-Line Scheduling of Real-Time Services for Cloud Computing", IEEE, 2010.
[12] J. Yu and R. Buyya, “Workflow Scheduling Algorithms for Grid Computing”, Technical Report, GRIDS-TR2007-10, Grid Computing and Distributed Systems Laboratory, The University of Melbourne, Australia, May 2007.
[13] Anju Bala, Dr. Inderveer Chana, "A Survey of Various Workflow Scheduling Algorithms in Cloud Environment", 2nd National Conference on Information and Communication Technology (NCICT), 2011, Proceedings published in International Journal of Computer Applications® (IJCA).
[14] S. H. Jang, T. Y. Kim, J. K. Kim, and J. S. Lee, "The study of genetic algorithm-based task scheduling for cloud computing," International Journal of Control and Automation, vol. 5, pp. 157-162, 2012.
[15] T. Goyal and A. Agrawal, "Host Scheduling Algorithm Using Genetic Algorithm In Cloud Computing Environment," International Journal of Research in Engineering & Technology (IJRET) Vol, vol. 1, 2013.
[16] R. Buyya, R. Ranjan, and R. N. Calheiros, "Modeling and simulation of scalable Cloud computing environments and the CloudSim toolkit: Challenges and opportunities," in High Performance Computing & Simulation, 2009. HPCS'09. International Conference on, 2009, pp. 111.
[17] A.I.Awad, N.A.El-Hefnawy and H.M.Abdel_kader,” Dynamic Multiobjective task scheduling in Cloud Computing based on Modified particle swarm optimization”, Advances in Computer Science: an International Journal, Vol. 4, Issue 5, No.17 , September 2015
[18] VG.Ravindhren and Dr. S. Ravimaran ,” Responsive Multi-objective Load Balancing Transformation Using Particle Swarm Optimization in Cloud Environment”, J o u r n a l o f A d v a n c e s i n c h e m i s t r y, V o l u m e 1 2 N u m b e r 1 5, I S S N 2 3 2 1 - 8 0 7 X.
[19] Shikha Chaudhary ,Saroj Hiranwal ,C. P. Gupta,” Review on Multiobjective Task Scheduling in Cloud Computing using Nature Inspired Algorithms”, International Journal of Emerging Research in Management &Technology, ISSN: 2278-9359 (Volume-6, Issue-8).
[20] Atul Vikas Lakraa, Dharmendra Kumar Yadav ,” Multi-Objective Tasks Scheduling Algorithm for Cloud ComputingThroughput Optimization”, International Conference on Intelligent Computing, Communication & Convergence, Procedia Computer Science 48 ( 2015 ) 107 – 113.
[21] Sourabh Budhiraja, Dr. Dheerendra Singh, “An Efficient Approach for Task Scheduling Based on Multi-Objective Genetic Algorithm inCloud Computing Environment”, JCSC VOLUME 5 • NUMBER 2 JULY-SEPT 2014 PP. 110115 ISSN-0973-7391.
[22] Majid Habibi, Nima Jafari Navimipour,” Multi-Objective Task Scheduling in Cloud Computing Using an Imperialist Competitive Algorithm”, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 7, No. 5, 2016.
[23] Vanita Dandhwani, Dr.Vipul Vekariya,” Multi-Objective Task Scheduling using K-mean Algorithm in Cloud Computing”, International Journal of Innovative Research in Computer and Communication Engineering, Vol. 4, Issue 11, November 2016.
[24] R K Jena,” Multi objective Task Scheduling in Cloud Environment Using Nested PSO Framework”, Procedia Computer Science 57 ( 2015 ) 1219 – 1227.
[25] Negar Dordaie , Nima Jafari Navimipour., “A hybrid particle swarm optimization and hill climbing algorithm for task scheduling in the cloud environment,”KICS (2017) 199-202.
[26] Dorigo M. and Blum C., “Ant Colony Optimization Theory: A Survey,” in Theoretical Computer Science, vol. 344, no. 2, pp. 243-278, 2005.
[27] Bonabeau E., Dorigo M., and theraulaz G., Swarm Intelligence: From Natural to Artificial Intelligence, Oxford University Press, New York, USA, 1999.