With the Internet of Things (IoT), applications should interact with a huge number of devices and retrieve context data produced by those objects, which have to be discovered and selected a priori. Due to the number, heterogeneity, and dynamicity of resources, discovery services are required to consider many selection criteria, e.g., device capabilities, location, context data type, contextual situations, and quality. In this paper, we describe QoDisco, a semantic-based discovery service that addresses this requirement in IoT. QoDisco is composed of a set of repositories storing resource descriptions according to an ontology-based information model and it provides multi-attribute and range querying capabilities. We have evaluated different approaches to reduce the inherent cost of semantic search, namely parallel interactions with multiple repositories and publish-subscribe interactions. This paper also reports the results of some performance experiments on QoDisco with respect to these approaches to handle resource discovery requests in IoT.

中文翻译：

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物联网的基于语义的发现服务

借助物联网（IoT），应用程序应与大量设备交互，并检索那些对象产生的上下文数据，必须先发现并选择这些数据。由于资源的数量，异构性和动态性，发现服务需要考虑许多选择标准，例如设备功能，位置，上下文数据类型，上下文情况和质量。在本文中，我们描述了QoDisco，这是一种基于语义的发现服务，可满足IoT中的这一要求。QoDisco由一组存储库组成，这些存储库根据基于本体的信息模型存储资源描述，并提供多属性和范围查询功能。我们评估了各种方法来减少语义搜索的固有成本，即与多个存储库的并行交互和发布-订阅交互。本文还报告了QoDisco上有关处理物联网中资源发现请求的这些方法的一些性能实验的结果。