Lucas Martínez Néstor, Martínez José-Fernán, Hernández Díaz Vicente
Centro de Investigación en Tecnologías Software y Sistemas Multimedia para la Sostenibilidad (CITSEM), Universidad Politécnica de Madrid (UPM), Edificio La Arboleda, Campus Sur, Carretera de Valencia km.7, Madrid 28031, Spain.
Sensors (Basel). 2014 Dec 1;14(12):22737-53. doi: 10.3390/s141222737.
Wireless Sensor Networks (WSNs) are generally used to collect information from the environment. The gathered data are delivered mainly to sinks or gateways that become the endpoints where applications can retrieve and process such data. However, applications would also expect from a WSN an event-driven operational model, so that they can be notified whenever occur some specific environmental changes instead of continuously analyzing the data provided periodically. In either operational model, WSNs represent a collection of interconnected objects, as outlined by the Internet of Things. Additionally, in order to fulfill the Internet of Things principles, Wireless Sensor Networks must have a virtual representation that allows indirect access to their resources, a model that should also include the virtualization of event sources in a WSN. Thus, in this paper a model for a virtual representation of event sources in a WSN is proposed. They are modeled as internet resources that are accessible by any internet application, following an Internet of Things approach. The model has been tested in a real implementation where a WSN has been deployed in an open neighborhood environment. Different event sources have been identified in the proposed scenario, and they have been represented following the proposed model.
无线传感器网络(WSN)通常用于从环境中收集信息。收集到的数据主要传送到汇聚节点或网关,这些节点成为应用程序可以检索和处理此类数据的端点。然而,应用程序还期望无线传感器网络具备事件驱动的操作模式,以便在发生某些特定环境变化时能够得到通知,而不是持续分析定期提供的数据。在任何一种操作模式下,无线传感器网络都代表着相互连接的对象的集合,正如物联网所概述的那样。此外,为了符合物联网的原则,无线传感器网络必须有一个虚拟表示,以便间接访问其资源,该模型还应包括无线传感器网络中事件源的虚拟化。因此,本文提出了一种无线传感器网络中事件源的虚拟表示模型。按照物联网的方法,将它们建模为任何互联网应用程序都可访问的互联网资源。该模型已在一个实际实现中进行了测试,其中在一个开放的社区环境中部署了一个无线传感器网络。在所提出的场景中识别出了不同的事件源,并按照所提出的模型对它们进行了表示。