An efficient population-based multi-objective task scheduling approach in fog computing systems

With the rapid development of Internet of Things (IoT) technologies, fog computing has emerged as an extension to the cloud computing that relies on fog nodes with distributed resources at the edge of network. Fog nodes offer computing and storage resources opportunities to resource-less IoT devices...

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Vydáno v:	Journal of cloud computing : advances, systems and applications Ročník 10; číslo 1; s. 53:1 - 53:31
Hlavní autoři:	Movahedi, Zahra, Defude, Bruno, Hosseininia, Amir mohammad
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 07.10.2021 Springer Nature B.V Hindawi Limited SpringerOpen
Témata:	Cloud computing Computation offloading Computer Communication Networks Computer Science Computer System Implementation Computer Systems Organization and Communication Networks Edge-cloud computing cooperation for task offloading in internet-of-things Energy consumption Fog computing Genetic algorithms Heuristic methods Information Systems Applications (incl.Internet) Integer programming Internet of Things Linear programming Meta-heuristic Multiple objective analysis Network latency Nodes Opposition-based learning Optimization Particle swarm optimization Quality of service architectures Scheduling Software Engineering/Programming and Operating Systems Special Purpose and Application-Based Systems Task scheduling Whale optimization algorithm Fog computing Internet of things Chaos theory Task scheduling Meta-heuristic Whale optimization algorithm Opposition-based learning
ISSN:	2192-113X, 2192-113X
On-line přístup:	Získat plný text
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