AI 中文总结
该研究提出结合MDSD与SWT的方法，实现WSN的非侵入式语义丰富化，可降低部署维护成本、支持大规模管理，且计算开销低，能部分自动化配置WSN。
AI 中文摘要
本文提出了一种用于无线传感器网络（WSNs）中测量传感器数据语义丰富化的高效方法，该方法通过桥接模型驱动软件开发（MDSD）与语义网技术（SWT）实现。我们的方法利用SWT增强数据互操作性，促进数据共享与复用；基于模型且与类型无关的配置降低了WSN部署与维护的整体工作量，这类工作传统上复杂且耗时。所提方法通过在WSN配置与管理中应用SWT解决了大规模WSN管理问题，无需专业知识。此外，我们提出了通用架构与实现方案，并辅以一个说明性用例的实操描述。实验结果表明，我们的基于模型的方法可实现非侵入式语义丰富化，计算开销为亚毫秒级，还能对WSN进行部分自动化配置。
英文摘要
The paper presents an efficient approach to the semantic enrichment of measured sensor data in Wireless Sensor Networks (WSNs), by bridging techniques from Model-driven Software Development (MDSD) and Semantic Web Technology (SWT). Our approach reinforces data interoperability, fostering data sharing and reuse, by utilizing SWT. Model-based and type-agnostic configuration reduces the overall effort for WSN setup and maintenance, which are traditionally complex and time-consuming tasks. The presented approach addresses the problem of large-scale WSN management through the application of SWT in WSN configuration and management without requiring expert knowledge. Additionally, we present a generic architecture and an implementation which is also supplemented by hands-on descriptions of an illustrative use case. Our experimental results demonstrate that our model-based approach provides non-intrusive semantic enrichment with sub-millisecond computational overhead, as well as partially automated configuration of WSNs.
CommentsPublished in: 2020 46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)
Journal ref2020 46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), Portoroz, Slovenia, 2020, pp. 561-568
DOI：10.1109/SEAA51224.2020.00092
