Mobile-Edge-Computing-Based Hierarchical Machine Learning Tasks Distribution for IIoT

• Published in: IEEE internet of things journal Vol. 7; no. 3; pp. 2169 - 2180
• Main Authors: Yang, Bo, Cao, Xuelin, Li, Xiangfang, Zhang, Qinqing, Qian, Lijun
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.03.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Anomalies; Bandwidths; Cognitive tasks; Computation offloading; Computational modeling; Data integrity; Data models; Data processing; Delay; Delays; Edge computing; Industrial applications; Industrial Internet of Things (IIoT); Internet of Things; Machine learning; machine learning (ML); Mobile computing; mobile edge computing (MEC); Optimization; Robot sensing systems; Task analysis
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2019.2959035

In this article, we propose a novel framework of mobile edge computing (MEC)-based hierarchical machine learning (ML) tasks distribution for the Industrial Internet of Things. It is assumed that a batch of ML tasks, such as anomaly detection, need to be executed timely in an MEC setting, where the d...