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Fast self-configuration in service-oriented Smart Environments for real-time applications

机译:在面向服务的智能环境中针对实时应用的快速自配置

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摘要

Smart Environments (SE) aim to satisfy the experience of individuals by the provision of systems, services and devices. Although many approaches may be followed in order to build a SE, a service-based design is the most promising one nowadays. In these architectures, both physical devices and even humans may provide low-level services based on their capabilities. These low-level services are composed and connected in order to create high-level services, employed by managers to describe the behavior of the SE. This composition process traditionally requires the human intervention, so changes in services are not automatic. However SE should operate at real-time, thus the collection of available services must be always updated. In the state of the art this challenge has been only partially covered, and proposed solutions are still heavy and manual. Therefore, in this work we propose a new fast semi-automatic self-configuration (and automatic self-adaptation) technology for service-oriented SE. The proposed technology is based on the definition of templates at different levels which are related by means of semantic information. Moreover, simple binary mathematical operations are included in order to reduce the convergence time and improve the scalability. A first reduced extension for hybrid approaches (including both humans and physical devices) is also provided. Finally, an experimental validation is conducted in order to evaluate the convergence time of the proposed solution in different scenarios, and demonstrate it is scalable towards future deployments involving thousands of devices and (possibly) humans.
机译:智能环境(SE)旨在通过提供系统,服务和设备来满足个人的体验。尽管可以采用许多方法来构建SE,但基于服务的设计是当今最有前途的设计。在这些体系结构中,物理设备甚至人类都可以根据其功能提供低级服务。这些低层服务被组合并连接在一起,以创建高层服务,管理者使用它们来描述SE的行为。传统上,此组合过程需要人工干预,因此服务更改不是自动的。但是SE应该实时运行,因此必须始终更新可用服务的集合。在现有技术中,该挑战仅被部分解决,并且所提出的解决方案仍然繁琐且手动。因此,在这项工作中,我们为面向服务的SE提出了一种新的快速半自动自配置(和自动自适应)技术。所提出的技术基于通过语义信息相关联的不同级别的模板的定义。此外,为了减少收敛时间并提高可伸缩性,还包括简单的二进制数学运算。还提供了混合方法(包括人和物理设备)的第一个简化扩展。最后,进行了实验验证,以评估所提出的解决方案在不同情况下的收敛时间,并证明它可扩展到涉及数千个设备和(可能)人类的未来部署。

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