Comparative analysis of task level heuristic scheduling algorithms in cloud computing

被引:13
作者
Hamid, Laiba [1 ]
Jadoon, Asmara [1 ]
Asghar, Hassan [2 ,3 ]
机构
[1] Govt Girls Postgrad Coll 1, Dept Comp Sci, Abbottabad, Pakistan
[2] COMSATS Univ Islamabad, Dept Comp Sci, Abbottabad Campus, Abbottabad, Pakistan
[3] Hongik Univ, Dept Software & Commun Engn, Sejong, South Korea
关键词
Cloud computing; Scheduling algorithm; First come First serve; Min-min; Max-min; Round robin; Makespan;
D O I
10.1007/s11227-022-04382-x
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Cloud computing is a platform that provides many applications based on cloud infrastructure. It provides the facility of using different resources such as data storage, databases, networking, etc. The main problem in the cloud computing environment is task scheduling which plays an important role in optimizing the total execution time. In this paper, a comparison of scheduling algorithms such as First Come First Serve, Round Robin, min-min and max-min is done based on makespan using workflows as datasets. Comparison is done in by increasing the number of virtual machines Workflowsim environment. Experimental results show a decrease in makespan as the number of Virtual Machines is increased. For CyberShake workflow First Come First Serve algorithm has performed 3.69% better than Round Robin, outperformed 13.38% than min-min, and has given 22.68% better results than max-min. In the case of Montage workflow, max-min has performed 26.73% better than First Come First Serve, 17.73% than Round Robin, and has given 4.63% better results than min-min.
引用
收藏
页码:12931 / 12949
页数:19
相关论文
共 42 条
[1]  
Agarwal, 2019, INT J COMPUT SCI ENG, V7, P981
[2]  
Al-Haboobi A. S., 2022, Int. J. Comput. Appl., V975, P8887
[3]   A Task Scheduling Algorithm With Improved Makespan Based on Prediction of Tasks Computation Time algorithm for Cloud Computing [J].
Al-Maytami, Belal Ali ;
Fan, Pingzhi ;
Hussain, Abir ;
Baker, Thar ;
Liatsist, Panos .
IEEE ACCESS, 2019, 7 :160916-160926
[4]   New Approach to Determine DDoS Attack Patterns on SCADA System Using Machine Learning [J].
Alhaidari, Fahd A. ;
Al-Dahasi, Ezaz Mohammed .
2019 INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION SCIENCES (ICCIS), 2019, :541-546
[5]  
Alworafi MA, 2016, 2016 INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONICS, COMMUNICATION, COMPUTER AND OPTIMIZATION TECHNIQUES (ICEECCOT), P208, DOI 10.1109/ICEECCOT.2016.7955216
[6]  
[Anonymous], 2012, International Journal of Engineering Research and Applications (IJERA)
[7]  
[Anonymous], 2016, 2016 INT C EM TRENDS
[8]   Task scheduling techniques in cloud computing: A literature survey [J].
Arunarani, A. R. ;
Manjula, D. ;
Sugumaran, Vijayan .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2019, 91 :407-415
[9]  
Asghar H, 2021, J SUPERCOMPUT, V77, P7184, DOI 10.1007/s11227-020-03491-9
[10]   A hybrid genetic algorithm for scientific workflow scheduling in cloud environment [J].
Aziza, Hatem ;
Krichen, Saoussen .
NEURAL COMPUTING & APPLICATIONS, 2020, 32 (18) :15263-15278