Cruz Huacarpuma Ruben, de Sousa Junior Rafael Timoteo, de Holanda Maristela Terto, de Oliveira Albuquerque Robson, García Villalba Luis Javier, Kim Tai-Hoon
Cybersecurity INCT Unit 6, Decision Technologies Laboratory-LATITUDE, Electrical Engineering Department (ENE), Technology College, University of Brasília (UnB), Brasília-DF, CEP 70910-900, Brazil.
Department of Computer Science, University of Brasília (UnB), Brasília-DF, CEP 70910-900, Brazil.
Sensors (Basel). 2017 Apr 27;17(5):977. doi: 10.3390/s17050977.
The development of the Internet of Things (IoT) is closely related to a considerable increase in the number and variety of devices connected to the Internet. Sensors have become a regular component of our environment, as well as smart phones and other devices that continuously collect data about our lives even without our intervention. With such connected devices, a broad range of applications has been developed and deployed, including those dealing with massive volumes of data. In this paper, we introduce a Distributed Data Service (DDS) to collect and process data for IoT environments. One central goal of this DDS is to enable multiple and distinct IoT middleware systems to share common data services from a loosely-coupled provider. In this context, we propose a new specification of functionalities for a DDS and the conception of the corresponding techniques for collecting, filtering and storing data conveniently and efficiently in this environment. Another contribution is a data aggregation component that is proposed to support efficient real-time data querying. To validate its data collecting and querying functionalities and performance, the proposed DDS is evaluated in two case studies regarding a simulated smart home system, the first case devoted to evaluating data collection and aggregation when the DDS is interacting with the UIoT middleware, and the second aimed at comparing the DDS data collection with this same functionality implemented within the Kaa middleware.
物联网(IoT)的发展与连接到互联网的设备数量和种类的显著增加密切相关。传感器已成为我们环境中的常规组件,还有智能手机和其他设备,即使在我们没有干预的情况下也能持续收集有关我们生活的数据。借助此类连接设备,已经开发并部署了广泛的应用程序,包括处理大量数据的应用程序。在本文中,我们引入了一种分布式数据服务(DDS),用于为物联网环境收集和处理数据。这种DDS的一个核心目标是使多个不同的物联网中间件系统能够从一个松耦合的提供者那里共享通用数据服务。在此背景下,我们提出了一种DDS功能的新规范以及在该环境中方便高效地收集、过滤和存储数据的相应技术概念。另一个贡献是提出了一个数据聚合组件,以支持高效的实时数据查询。为了验证其数据收集和查询功能及性能,在关于模拟智能家居系统的两个案例研究中对所提出的DDS进行了评估,第一个案例致力于评估DDS与UIoT中间件交互时的数据收集和聚合,第二个案例旨在将DDS数据收集与此相同功能在Kaa中间件中实现的情况进行比较。