Paper Info
Title
Autonomous IoT Device Management Systems: Structured Review and Generalized Cognitive Model
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 are first organized and analyzed according to a synthesized taxonomy of observed adaptation mechanisms, and then combined with the 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.
Year
DOI
Venue
2021
10.1109/JIOT.2020.3035389
IEEE Internet of Things Journal
Keywords
DocType
Volume
Adaptation mechanisms,adaptive management,artificial intelligence,autonomous device management,cognitive computing,constrained devices,Internet of Things (IoT),IoT architecture,machine learning (ML),self-management,situation awareness
Journal
8
Issue
ISSN
Citations 
6
2327-4662
1
PageRank 
References 
Authors
0.37
0
3
Name
Order
Citations
PageRank
Anders Eivind Braten1273.87
Frank Alexander Kraemer226221.13
David Palma3728.58