Low-time complexity and low-cost binary particle swarm optimization algorithm for task scheduling and load balancing in cloud computing

With the increasing large number of cloud users, the number of tasks is growing exponentially. Scheduling and balancing these tasks amongst different heterogeneous virtual machines (VMs) under constraints such as, low makespan, high resource utilization rate, low execution cost and low scheduling ti...

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Veröffentlicht in:	Applied intelligence (Dordrecht, Netherlands) Jg. 49; H. 9; S. 3308 - 3330
Hauptverfasser:	Mapetu, Jean Pepe Buanga, Chen, Zhen, Kong, Lingfu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.09.2019 Springer Nature B.V
Schlagworte:	Algorithms Artificial Intelligence Cloud computing Completion time Computer Science Computing costs Heuristic Heuristic methods Heuristic task scheduling Load balancing Low cost Machines Manufacturing Mechanical Engineering Optimization Particle swarm optimization Processes Production scheduling Scheduling Task complexity Virtual environments Task scheduling Binary particle swarm optimization Cloud computing Load balancing Time complexity Completion time
ISSN:	0924-669X, 1573-7497
Online-Zugang:	Volltext
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