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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Vydané v:	Applied intelligence (Dordrecht, Netherlands) Ročník 49; číslo 9; s. 3308 - 3330
Hlavní autori:	Mapetu, Jean Pepe Buanga, Chen, Zhen, Kong, Lingfu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.09.2019 Springer Nature B.V
Predmet:	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
On-line prístup:	Získať plný text
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