A Comparative Study on GA-based Scheduling on Cloud Computing

dc.contributor.author	Rawshan, Lamisha
dc.contributor.author	Rahman, Tasnim
dc.contributor.author	Begum, Afsana
dc.contributor.author	Hossain, Syeda Sumbul
dc.contributor.author	Bhuiyan, Touhid
dc.date.accessioned	2022-01-20T07:01:22Z
dc.date.available	2022-01-20T07:01:22Z
dc.date.issued	2020
dc.identifier.uri	http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6831
dc.description.abstract	Cloud computing provides data storage and computing power based on user demand by assigning tasks to virtual resources. To deliver overall improved performance and meet challenges such as availability, resource utilization and reliability in the cloud, appropriate resource scheduling methods are needed. A number of metaheuristic optimization algorithms are used to solve the problem of resource scheduling. This work lists challenges and analyzes previous scheduling methods based on Genetic Algorithm (GA). It classifies the GA-based scheduling methods with respect to many parameters. At last, it presents the scopes of enhancement for future researchers.	en_US
dc.language.iso	en_US	en_US
dc.publisher	Scopus	en_US
dc.subject	metaheuristic optimization algorithms	en_US
dc.subject	Genetic Algorithm	en_US
dc.title	A Comparative Study on GA-based Scheduling on Cloud Computing	en_US
dc.type	Article	en_US