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Autonomous IoT Device Management Systems: Structured Review and Generalized Cognitive Model

Bråten, Anders Eivind; Kraemer, Frank Alexander; Palma, David
Peer reviewed, Journal article
Accepted version
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URI
https://hdl.handle.net/11250/2723413
Date
2020
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  • Institutt for informasjonssikkerhet og kommunikasjonsteknologi [1600]
  • Publikasjoner fra CRIStin - NTNU [20948]
Original version
10.1109/JIOT.2020.3035389
Abstract
Research on autonomous management for large-scale deployments of constrained devices is still a maturing field in the Internet of Things (IoT). Although much research has been conducted on how to achieve autonomous management in specific cases, there is a need for literature investigating which mechanisms can achieve such behavior in a generalized way. In this review, we present a comprehensive and structured study of the mechanisms for autonomous device management of constrained IoT devices in the light of management tasks, operational environment, network topology, resource constraints, scalability and management categories. Data extracted from 32 relevant cases is first organized and analyzed according to a synthesized taxonomy of observed adaptation mechanisms, and then combined with state-of-the-art models of autonomous operations, identifying common patterns for autonomous management. Based on our findings we substantiate best practices for designing and implementing solutions around adaptation mechanisms. We then present a generalized model for autonomous device management that describes and explains the processes required for autonomous operation, unifying the insights from previous works as one cohesive archetype.
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Journal
IEEE Internet of Things Journal

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