基于Node.js平台物联网Web服务的设计与实现

利用面向服务架构(SOA)的优势,可以解决开发人员与用户在物联网环境中面临的难题。提出了基于Node.js平台的Web服务设备配置文件(DPWS)实现方法,即Node.DPWS,Node.DPWS可在异构节点(包括资源有限的设备)上部署轻量级、高效且可扩展的Web服务。研究结果表明:通过在嵌入式设备上进行性能评估比较,Node.DPWS的性能优于WS4D-JMEDS工具包,Node.DPWS设备其平均响应时间为24.44ms,比SE和CDC快66.3%和53%。在查询Node.DPWS设备时,在12.22 s内即可完成500个请求的基准测试。Node.DPWS设备的响应速度更快,消耗内存更低。为实现新颖、更优服务物联网及其扩展性,可用性,互操作性提供技术参考。     

基于设备网络服务框架的微网监控构架与自适应服务方法

针对传统的基于客户机/服务器(C/S)模式的微网监控系统缺乏对动态网络的适应性支持和Multi-Agent安全性不足的问题,提出了基于新一代网络中间件——设备网络服务框架(DPWS)的微网分布式监控架构和自适应服务方法。根据微网的特点和要求建立了微网系统的网络监控模型。利用DPWS的"即插即用"机制解决了设备入网的自动识别、自动入网问题,通过服务调用和事件订阅服务实现了对目标数据和状态的实时观测,运用HTTPS方法确保了数据传输的安全性和完整性。软件开发与仿真证明该系统具有良好的动态性和自适应能力,能够实现对微网监控设备的智能化管理。     

基于DPWS与Petri网的机器人自适应监控架构与服务方法研究

针对当前分布式机器人监控网络系统存在的自适应能力差、实时性不高等问题,提出了一种基于设备网络服务构架(DPWS)与Petri网的分布式机器人自适应网络监控架构与服务方法。利用DPWS自主发现机制,实现监控网络结点的自动组网、动态配置和无缝链接;结合WSDL设备服务描述机制,为系统提供统一的服务接口,屏蔽底层机器人设备异构性。在此基础上,利用Petri网技术实现监控系统设备端的过程控制,提高系统整体的执行效率与实时性。以低压电器装配过程为对象,建立了系统仿真模型,开发了监控系统应用软件。实验研究结果表明,本方法可有效提高分布式机器人监控过程的自适应服务性能与执行效率,可为相关监控系统研发提供有益技术支持。     

SOA in reconfigurable supply chains: A research roadmap

Originally coming from the business world, service-oriented architecture (SOA) paradigm is expanding its range of application into several different environments. Industrial automation is increasingly interested on adopting it as a unifying approach with several advantages over traditional automation. In particular, the paradigm is well indicated to support agile and reconfigurable supply chains due to its dynamic nature. In this domain, the main goals are short time-to-market, fast application (re)configurability, more intelligent devices with lifecycle support, technology openness, seamless IT integration, etc. The current research challenges associated to the application of SOA into reconfigurable supply chains are enumerated and detailed with the aim of providing a roadmap into a major adoption of SOA to support agile reconfigurable supply chains.     

PLaTHEA: a marker‐less people localization and tracking system for home automation

Current smart spaces require more and more sophisticated sensors able to acquire the state of the environment in order to provide advanced and customized services. Among the most important environmental variables, locations of users and their identities represent a primary concern for smart home applications. Despite some years of investigation in indoor positioning, the availability of systems designed as components pluggable into complex home automation platforms is limited. We present People Localization and Tracking for HomE Automation (PLaTHEA), a vision‐based indoor localization system specifically tailored for Ambient Assisted Living applications. PLaTHEA features a novel technique to acquire a stereo video stream from a couple of independent (and not synchronized) network‐attached cameras, thus easing its physical deployment. The input stream is processed by integrating well‐known techniques with a novel tracking approach targeted to indoor spaces. The system has a modular architecture that offers clear interfaces exposed as Web services, and it can run on off‐the‐shelf and cheap hardware (both in terms of sensing devices and computing units). We evaluated PLaTHEA in real usage conditions and reported the measured performance in terms of precision and accuracy. Low light, crowded and large monitored environments might slightly decrease the performance of the system; nevertheless, the results here presented show that it is perfectly suitable to be employed in the typical domestic day‐to‐day life settings. Copyright © 2014 John Wiley & Sons, Ltd.     

服务导向设备:下一步会迈向哪里

通过正确使用行业标准以及支持这些标准的操作系统,OEM可以实现众多服务导向的设备.此外,在快速变化、竞争激烈的市场中,设备制造商必需依赖工具和平台,最大限度地实现其服务导向设备的价值和特色.