Tasks Scheduling and Resource Allocation in Fog Computing Based on Containers for Smart Manufacturing

Fog computing has been proposed as an extension of cloud computing to provide computation, storage, and network services in network edge. For smart manufacturing, fog computing can provide a wealth of computational and storage services, such as fault detection and state analysis of devices in assemb...

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Vydáno v:IEEE transactions on industrial informatics Ročník 14; číslo 10; s. 4712 - 4721
Hlavní autoři: Yin, Luxiu, Luo, Juan, Luo, Haibo
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.10.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Assembly lines
Cloud computing
Concurrency
Container
Containers
Edge computing
Fault detection
fog computing
Processor scheduling
Resource allocation
Resource management
Resource scheduling
Scheduling algorithms
Servers
smart industry
Task analysis
Task scheduling
ISSN:1551-3203, 1941-0050
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Shrnutí:Fog computing has been proposed as an extension of cloud computing to provide computation, storage, and network services in network edge. For smart manufacturing, fog computing can provide a wealth of computational and storage services, such as fault detection and state analysis of devices in assembly lines, if the middle layer between the industrial cloud and the terminal device is considered. However, limited resources and low-delay services hinder the application of new virtualization technologies in the task scheduling and resource management of fog computing. Thus, we build a new task-scheduling model by considering the role of containers. Then, we construct a task-scheduling algorithm to ensure that the tasks are completed on time and the number of concurrent tasks for the fog node is optimized. Finally, we propose a reallocation mechanism to reduce task delays in accordance with the characteristics of the containers. The results showed that our proposed task-scheduling algorithm and reallocation scheme can effectively reduce task delays and improve the concurrency number of the tasks in fog nodes.
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content type line 14
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2018.2851241