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SPARQL for Networks of Embedded Systems

机译:适用于嵌入式系统网络的SPARQL

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In the Internet of Things (IoT), small-scale embedded devices monitor and control real-world objects with different kinds of sensors and actuators. Often, devices communicate measurements and states using proprietary encodings, with the benefit of having all data stored in a central location, e.g., the Cloud. The drawbacks are that all data needs to be collected in advance, even if it is not used afterwards, and that nonstandard protocols make it hard to extend existing networks with new devices. In contrast, the Semantic Web (or Web of Data) represents the successful efforts towards linking and sharing data over the Web. The cornerstones of the Web of Data are RDF as data format and SPARQL as de-facto standard query language. Recent trends show the evolution of the integration of these two efforts into the Web of Things. We propose to elevate embedded devices to first-class citizens of the Web of Things by allowing storage and processing of RDF data. Our framework abstracts from individual deployments to represent them as common data sources in line with the ideas behind the Semantic Web. This includes the execution of SPARQL queries over the data from a pool of embedded devices and/or external data sources. Handling verbose RDF data and executing SPARQL queries in an embedded network pose major challenges to minimize the involved processing and communication cost. We therefore present an in-network query processor aiming to push processing steps onto devices. We demonstrate the practical application and the potential benefits of our framework in an evaluation using a real-world deployment and a range of SPARQL queries stemming from common use cases of the Web of Things.
机译:在物联网(物联网)(IOT),小规模嵌入式设备监控和控制具有不同种类的传感器和执行器的现实世界对象。通常,设备使用专有编码传送测量和状态,其具有存储在中心位置的所有数据,例如云。缺点是所有数据都需要提前收集,即使之后不使用,并且非标准协议使其难以扩展现有网络与新设备。相比之下,语义Web(或数据网)代表了在Web上连接和共享数据的成功努力。数据Web的基石是RDF作为数据格式和SPARQL作为De-Facto标准查询语言。最近的趋势表明这两种努力集成到事物网站中的演变。我们建议通过允许存储和处理RDF数据来将嵌入式设备提升到事物Web的一流公民。我们的框架摘要来自个人部署,以符合语义网络背后的想法,将它们代表它们作为常见数据源。这包括从嵌入式设备和/或外部数据源池中的数据执行SPARQL查询。处理详细的RDF数据并在嵌入式网络中执行SPARQL查询构成重大挑战,以最大限度地减少涉及的处理和通信成本。因此,我们展示了一个网络内查询处理器,旨在将处理步骤推入设备上。我们展示了使用现实世界部署的评估中框架的实际应用和框架的潜在好处,以及一系列源于事物的常见用例。

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