DocumentCode :
719117
Title :
An empirical study of most fit, max-min and priority task scheduling algorithms in cloud computing
Author :
Taneja, Bhawna
Author_Institution :
Dept. of Comput. Sci. & Applic., Kurukshetra Univ., Kurukshetra, India
fYear :
2015
fDate :
15-16 May 2015
Firstpage :
664
Lastpage :
667
Abstract :
Cloud computing is envisioned to provide each IT enabled service as a utility. From hardware to software, it is committed to fulfill all kind of needs with regard to computation, storage, development etc. at cost-effective and efficient manner. The efficient delivery of services in a cloud largely depends on how it schedules the user jobs (cloudlets) over its resources. A plenty of task scheduling algorithms are available for a cloud provider to choose from. This paper selects three most versatile and fundamental task scheduling algorithms i.e. Most Fit, Max-Min and Priority algorithm to study their comparative performance. From the practical aspect, these algorithms are simulated over cloudsim 3.0.3 toolkit with variable workload circumstances. A set of metrics is also calculated and a comparative assessment of the above mentioned algorithms has been done on the basis of these metrics.
Keywords :
cloud computing; minimax techniques; virtual machines; cloud computing; max-min algorithm; most fit algorithm; priority task scheduling algorithm; Cloud computing; Measurement; Quality of service; Resource management; Scheduling; Scheduling algorithms; Cloud Computing Environment; Data; Service Level Agreement; Virtual Machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing, Communication & Automation (ICCCA), 2015 International Conference on
Conference_Location :
Noida
Print_ISBN :
978-1-4799-8889-1
Type :
conf
DOI :
10.1109/CCAA.2015.7148457
Filename :
7148457
Link To Document :
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