BlazeAIoT: A Modular Multi-Layer Platform for Real-Time Distributed Robotics Across Edge, Fog, and Cloud Infrastructures

2026-01-09

arXiv.org

AI Summary

This work addresses the challenges of real-time performance, scalability, and interoperability in distributed robotic systems operating within heterogeneous edge-fog-cloud environments. The authors propose a modular, multi-layer platform that unifies edge, fog, and cloud resources under a cohesive architecture, featuring innovative multi-tier configuration services, dynamic adaptive data bridging, and hierarchical rate-limiting mechanisms to enable resilient service deployment and system health maintenance even under incomplete network topologies. Built on Kubernetes, the platform integrates protocol proxies for DDS, Kafka, Redis, and ROS 2 to facilitate seamless cross-layer communication and interoperability. Experimental validation in navigation and AI-driven large-scale messaging scenarios demonstrates its low latency, high robustness, and cost-aware scalability, making it well-suited for IoT applications such as smart factories and smart cities.

Technology Category

• Intelligent Robots: Multi-Robot Systems
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Application Domains: Internet of Things, Sensor Networks & Smart Cities

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Federated Web and WoT systems, including distributed, federated and edge-based data processing
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Economics, Online Markets and Human Computation: Economics and fairness of platforms and recommendation systems

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 validated through robotics scenarios involving navigation and artificial intelligence-driven large-scale message processing, demonstrating robust performance under real-time constraints. Results highlight BlazeAIoT's ability to dynamically allocate services across incomplete topologies, maintain system health, and minimize latency, making it a cost-aware, scalable solution for robotics and broader IoT applications, such as smart cities and smart factories.

Problem

• distributed robotics
• real-time constraints
• edge-fog-cloud integration
• heterogeneous infrastructures
• modular platform

Innovation

• modular multi-layer architecture
• real-time distributed robotics
• adaptive data distribution
• Kubernetes-based orchestration
• broker interoperability