Landscape of IoT Patterns
Hironori Washizaki, Nobukazu Yoshioka, Atsuo Hazeyama, Takehisa Kato,, Haruhiko Kaiya, Shinpei Ogata, Takao Okubo, Eduardo B. Fernandez
TL;DR
This paper analyzes the classification and adoption challenges of IoT design and architecture patterns, providing insights and directions for improving their publication and utilization in IoT system development.
Contribution
It offers a comprehensive analysis of published IoT patterns across multiple dimensions and suggests improvements for their classification and adoption.
Findings
Many IoT patterns are not well classified.
Poor classification hinders pattern adoption.
The paper outlines directions for better publishing and adoption.
Abstract
Patterns are encapsulations of problems and solutions under specific contexts. As the industry is realizing many successes (and failures) in IoT systems development and operations, many IoT patterns have been published such as IoT design patterns and IoT architecture patterns. Because these patterns are not well classified, their adoption does not live up to their potential. To understand the reasons, this paper analyzes an extensive set of published IoT architecture and design patterns according to several dimensions and outlines directions for improvements in publishing and adopting IoT patterns.
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Taxonomy
TopicsIoT and Edge/Fog Computing · Context-Aware Activity Recognition Systems · Data Stream Mining Techniques