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

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.

Automated summary

This study provides a comprehensive review of autonomous device management for large-scale deployments of constrained devices in the IoT field, covering various aspects such as management tasks, operational environment, network topology, resource constraints, scalability, and management categories. It identifies common patterns for autonomous management and presents a generalized model that unifies previous insights, offering best practices for designing and implementing solutions around adaptation mechanisms.