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Big data-driven scheduling optimization algorithm for Cyber–Physical Systems based on a cloud platform

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成果类型:
期刊论文
作者:
Niu, Chao*;Wang, Lizhou
通讯作者:
Niu, Chao
作者机构:
[Niu, Chao] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Hubei, Peoples R China.
[Wang, Lizhou] Taiyuan Univ Technol, Sch Big Data, Taiyuan 030024, Shanxi, Peoples R China.
通讯机构:
[Niu, Chao] C
Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Hubei, Peoples R China.
语种:
英文
关键词:
Big data-driven;Cloud platform;Cyber–Physical Systems;Scheduling optimization algorithm
期刊:
Computer Communications
ISSN:
0140-3664
年:
2022
卷:
181
页码:
173-181
机构署名:
本校为第一且通讯机构
院系归属:
信息管理学院
摘要:
In this paper, we study big data-driven Cyber–Physical Systems (CPS) through cloud platforms and design scheduling optimization algorithms to improve the efficiency of the system. A task scheduling scheme for large-scale factory access under cloud–edge collaborative computing architecture is proposed. The method firstly merges the directed acyclic graphs on cloud-side servers and edge-side servers; secondly, divide the tasks using a critical path-based partitioning strategy to effectively improve the allocation accuracy; then achieves load ba...

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