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http://dx.doi.org/10.9717/kmms.2020.23.3.476

Design of Block-based Modularity Architecture for Machine Learning  

Oh, Yoosoo (Department of Artificial Intelligence, School of ICT Convergence, Daegu University)
Publication Information
Journal of Korea Multimedia Society / v.23, no.3, 2020 , pp. 476-482 More about this Journal
Abstract
In this paper, we propose a block-based modularity architecture design method for distributed machine learning. The proposed architecture is a block-type module structure with various machine learning algorithms. It allows free expansion between block-type modules and allows multiple machine learning algorithms to be organically interlocked according to the situation. The architecture enables open data communication using the metadata query protocol. Also, the architecture makes it easy to implement an application service combining various edge computing devices by designing a communication method suitable for surrounding applications. To confirm the interlocking between the proposed block-type modules, we implemented a hardware-based modularity application system.
Keywords
Machine Learning; Block Module; Modularity; Edge Computing; IoT;
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Times Cited By KSCI : 2  (Citation Analysis)
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