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一种用于最小化时间和能量的物联网-雾-云系统中的最优工作流调度。

An optimal workflow scheduling in IoT-fog-cloud system for minimizing time and energy.

作者信息

Rateb Roqia, Hadi Ahmed Adnan, Tamanampudi Venkata Mohit, Abualigah Laith, Ezugwu Absalom E, Alzahrani Ahmed Ibrahim, Alblehai Fahad, Jia Heming

机构信息

Department of Computer Science, College of Information Technology, Al-Ahliyya Amman University, Amman, Jordan.

Artificial Intelligence Sciences Department, College of Sciences, Al-Mustaqbal University, 51001, Babil, Iraq.

出版信息

Sci Rep. 2025 Jan 29;15(1):3607. doi: 10.1038/s41598-025-86814-1.

DOI:10.1038/s41598-025-86814-1
PMID:39875513
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11775208/
Abstract

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.

摘要

如今，随着物联网（IoT）在全球的使用日益增加，各种工作流需要在计算平台上进行存储和处理。但这个问题导致计算资源提供商的成本增加，结果系统能耗（EC）也降低了。因此，本文研究了雾云环境中物联网设备的工作流调度问题，其主要目标是在优先级、截止日期和可靠性的约束下，降低计算系统的能耗并减少工作流的完工时间（MST）。因此，为了实现这些目标，使用天鹰座和沙丁鱼群算法（ASSA）的组合来选择最佳虚拟机（VM）以执行工作流。所以，在ASSA执行的每次迭代中，ASSA会选择一些VM。然后通过使用减少完工时间（RMST）技术，在保持可靠性和截止日期的同时，减少所选VM上工作流的MST。接着，对RMST的输出使用VM合并和动态电压频率缩放（DVFS）技术，分别降低静态和动态能耗。实验结果表明，与先前方法相比，该方法是有效的。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f33d/11775208/f56c645123f7/41598_2025_86814_Figa_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f33d/11775208/48fcc4225249/41598_2025_86814_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f33d/11775208/ee2f1591e568/41598_2025_86814_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f33d/11775208/b4cf5e777a89/41598_2025_86814_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f33d/11775208/a3231baa50b9/41598_2025_86814_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f33d/11775208/888ea905621b/41598_2025_86814_Fig12_HTML.jpg
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