面向物联网应用的空间感知发布-订阅中间件
A Spatially-Aware Publish-Subscribe Middleware for IoT Applications
中文总结 AI 辅助
针对物联网应用中空间感知中间件缺失的问题，提出基于 MQTT5 协议的空间感知发布-订阅中间件，实验验证其效率高、开销小且可部署于现有 IoT 设备。
中文摘要 AI 辅助
空间与邻近感知是网络物理系统（CPS）和物联网（IoT）中实现高效通信的关键使能技术。然而，缺乏合适的中间件支持与标准化的空间感知机制，极大限制了位置相关应用的普及性。本文提出一种新方法，扩展该领域主流的基于主题的发布-订阅 messaging 模型，集成空间过滤与路由能力。该方法采用高度灵活的几何方法描述空间过滤器，支持表达力强且高效的空间订阅；几何世界模型与增强型基于主题的 broker 协同工作，实现受空间约束的消息分发。重要的是，此功能通过 MQTT5 协议实现，既不违反标准，也无需对现有客户端实现做任何修改。基于合成数据与真实世界数据的实验结果表明，该系统效率高、broker 处计算开销极小，且该方法在现有 IoT 设备上部署具备实际可行性。
英文摘要
Spatial and proximity awareness are critical enablers for efficient communication in Cyber-Physical Systems (CPS) and the Internet of Things (IoT). However, the lack of suitable middleware support and standardized mechanisms for spatial awareness significantly limits the pervasiveness of location-dependent applications. In this paper, we present a novel approach that extends topic-based publish-subscribe, a dominant messaging model in this domain, with integrated spatial filtering and routing capabilities. Our approach leverages a highly flexible geometric method for describing spatial filters, enabling expressive and efficient spatial subscriptions. A geometric world model operates together with an enhanced topic-based broker to realize spatially constrained message dissemination. Importantly, this functionality is achieved using the MQTT5 protocol without violating the standard or requiring any modifications to existing client implementations. Experimental results based on both synthetic and real-world data demonstrate strong system efficiency, minimal computational overhead at the broker, and the practical feasibility of deploying the approach on existing IoT devices.
