Um serviço de descoberta ciente de contexto para internet das coisas

Abstract

The Internet of Things (IoT) is an emergent paradigm characterized by a plethora of heterogeneous devices connected to the Internet. However, the high heterogeneity and the wide distribution of the available devices in IoT make difficult the adoption of this paradigm, with users facing challenges to find, select, and use resources in a fast, reliable, and user-friendly way. In this context, discovery services perform a key role, allowing clients (e.g., middleware platforms, end-users, and applications) to retrieve resources through the specification of search criteria containing attributes, such as the resource type, capabilities, location, quality of context (QoC) parameters, and etc. This dissertation introduces the QoDisco, a distributed discovery service to search resources by multiple attributes, range queries, and synchronous and asynchronous operations. Furthermore, QoDisco includes an ontology-based model for semantic description of resources (i.e., sensors and actuators), services, and data captured by sensors. This dissertation presents, in details, (i) the QoDisco architecture, (ii) its information model, (iii) a propotype implementation, (iv) and the integration of QoDisco with a middleware platform for IoT, EcoDiF. Lastly, this work presents a proof of concept in an urban pollution scenario and a qualitative avaliation of the QoDisco’s search procedure performance.