DCHG-TS: a deadline-constrained and cost-effective hybrid genetic algorithm for scientific workflow scheduling in cloud computing

Cloud infrastructures are suitable environments for processing large scientific workflows. Nowadays, new challenges are emerging in the field of optimizing workflows such that it can meet user’s service quality requirements. The key to workflow optimization is the scheduling of workflow tasks, which...

Full description

Saved in:

Bibliographic Details
Published in:	Cluster computing Vol. 24; no. 2; pp. 667 - 681
Main Authors:	Iranmanesh, Amir, Naji, Hamid Reza
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.06.2021 Springer Nature B.V
Subjects:	Big Data Cloud computing Computer Communication Networks Computer Science Critical path Efficiency Energy consumption Genetic algorithms Heuristic Load balancing Operating Systems Operators Optimization techniques Processor Architectures Scheduling Software services Task scheduling Workflow Workloads Cloud computing Genetic algorithm Workflow scheduling Heuristic
ISSN:	1386-7857, 1573-7543
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!