BlazeAIoT实现机器人在边缘、雾、云间的实时协同,支持动态调度与低延迟通信。
BlazeAIoT: A Modular Multi-Layer Platform for Real-Time Distributed Robotics Across Edge, Fog, and Cloud Infrastructures

- 采用Kubernetes+多协议消息中间件构建分层架构,支持跨异构环境无缝协作。
- 在导航与大规模AI处理场景中,实测延迟低于150ms,服务部署成功率超95%。
- 适合智能工厂、智慧城市等需实时响应的分布式机器人系统开发。
分布式机器人系统日益复杂,亟需统一集成边缘、雾和云计算层并满足严格实时性要求的平台。本文提出BlazeAIoT,一个模块化多层平台,旨在实现异构基础设施上分布式机器人的统一管理。该平台提供动态数据传输、可配置服务及集成监控功能,兼顾韧性、安全性和编程语言灵活性。其架构基于Kubernetes集群,融合DDS、Kafka、Redis与ROS2等消息代理的互操作性,并采用自适应数据分发机制优化跨环境通信与计算效率。解决方案包含多层配置服务、动态自适应数据桥接及分层速率限制,以应对大消息处理需求。通过导航与人工智能驱动的大规模消息处理等机器人场景验证,结果表明BlazeAIoT可在不完整拓扑下动态分配服务,保持系统健康状态,显著降低延迟,具备成本敏感、可扩展的特点,适用于机器人及更广泛的物联网应用,如智慧城市与智能工厂。
原文摘要 · Abstract (English)
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.
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