BlazeAIoT: A Modular Multi-Layer Platform for Real-Time Distributed Robotics Across Edge, Fog, and Cloud Infrastructures
Cedric Melancon, Julien Gascon-Samson, Maarouf Saad, Kuljeet Kaur, and Simon Savard

TL;DR
BlazeAIoT is a modular multi-layer platform that integrates edge, fog, and cloud infrastructures for real-time distributed robotics, offering dynamic data management, resilience, and scalability.
Contribution
It introduces a novel architecture combining Kubernetes, broker interoperability, and adaptive data mechanisms for seamless distributed robotics across heterogeneous environments.
Findings
Demonstrates robust real-time performance in navigation and AI scenarios.
Shows dynamic service allocation and latency minimization.
Validates scalability and resilience in large-scale robotics applications.
Abstract
The increasing complexity of distributed robotics has driven the need for platforms that seamlessly integrate edge, fog, and cloud computing layers while meeting strict real-time constraints. This paper introduces BlazeAIoT, a modular multi-layer platform designed to unify distributed robotics across heterogeneous infrastructures. BlazeAIoT provides dynamic data transfer, configurable services, and integrated monitoring, while ensuring resilience, security, and programming language flexibility. The architecture leverages Kubernetes-based clusters, broker interoperability (DDS, Kafka, Redis, and ROS2), and adaptive data distribution mechanisms to optimize communication and computation across diverse environments. The proposed solution includes a multi-layer configuration service, dynamic and adaptive data bridging, and hierarchical rate limiting to handle large messages. The platform is…
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Taxonomy
TopicsRobotics and Automated Systems · IoT and Edge/Fog Computing · Robotics and Sensor-Based Localization
