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An optimal workflow scheduling in IoT-fog-cloud system for minimizing time and energy
by
Ezugwu, Absalom E.
, Tamanampudi, Venkata Mohit
, Abualigah, Laith
, Hadi, Ahmed Adnan
, Rateb, Roqia
, Jia, Heming
, Alblehai, Fahad
, Alzahrani, Ahmed Ibrahim
in
639/4077
/ 639/766/259
/ Algorithms
/ Aquila-Salp Swarm Algorithm
/ Dynamic Voltage Frequency Scaling
/ Energy consumption
/ Fog
/ Fog-cloud computing
/ Humanities and Social Sciences
/ Internet of Things
/ multidisciplinary
/ Science
/ Science (multidisciplinary)
/ Workflow scheduling
2025
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An optimal workflow scheduling in IoT-fog-cloud system for minimizing time and energy
by
Ezugwu, Absalom E.
, Tamanampudi, Venkata Mohit
, Abualigah, Laith
, Hadi, Ahmed Adnan
, Rateb, Roqia
, Jia, Heming
, Alblehai, Fahad
, Alzahrani, Ahmed Ibrahim
in
639/4077
/ 639/766/259
/ Algorithms
/ Aquila-Salp Swarm Algorithm
/ Dynamic Voltage Frequency Scaling
/ Energy consumption
/ Fog
/ Fog-cloud computing
/ Humanities and Social Sciences
/ Internet of Things
/ multidisciplinary
/ Science
/ Science (multidisciplinary)
/ Workflow scheduling
2025
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An optimal workflow scheduling in IoT-fog-cloud system for minimizing time and energy
by
Ezugwu, Absalom E.
, Tamanampudi, Venkata Mohit
, Abualigah, Laith
, Hadi, Ahmed Adnan
, Rateb, Roqia
, Jia, Heming
, Alblehai, Fahad
, Alzahrani, Ahmed Ibrahim
in
639/4077
/ 639/766/259
/ Algorithms
/ Aquila-Salp Swarm Algorithm
/ Dynamic Voltage Frequency Scaling
/ Energy consumption
/ Fog
/ Fog-cloud computing
/ Humanities and Social Sciences
/ Internet of Things
/ multidisciplinary
/ Science
/ Science (multidisciplinary)
/ Workflow scheduling
2025
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An optimal workflow scheduling in IoT-fog-cloud system for minimizing time and energy
Journal Article
An optimal workflow scheduling in IoT-fog-cloud system for minimizing time and energy
2025
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Overview
Today, with the increasing use of the Internet of Things (IoT) in the world, various workflows that need to be stored and processed on the computing platforms. But this issue, causes an increase in costs for computing resources providers, and as a result, system Energy Consumption (EC) is also reduced. Therefore, this paper examines the workflow scheduling problem of IoT devices in the fog-cloud environment, where reducing the EC of the computing system and reducing the MakeSpan Time (MST) of workflows as main objectives, under the constraints of priority, deadline and reliability. Therefore, in order to achieve these objectives, the combination of Aquila and Salp Swarm Algorithms (ASSA) is used to select the best Virtual Machines (VMs) for the execution of workflows. So, in each iteration of ASSA execution, a number of VMs are selected by the ASSA. Then by using the Reducing MakeSpan Time (RMST) technique, the MST of the workflow on selected VMs is reduced, while maintaining reliability and deadline. Then, using VM merging and Dynamic Voltage Frequency Scaling (DVFS) technique on the output from RMST, the static and dynamic EC is reduced, respectively. Experimental results show the effectiveness of the proposed method compared to previous methods.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
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