In the Internet of Things, the relevance of data often depends on the geographic context of data producers and consumers. Today’s data distribution services, however, mostly focus on data content and not on geo-context, which would benefit many scenarios greatly. In this paper, we propose to use the geo-context information associated with devices to control data distribution. We define what geo-context dimensions exist and compare our definition with concepts from related work. By example, we discuss how geo-contexts enable new scenarios and evaluate how they also help to reduce unnecessary data distributions.
CITATION STYLE
Hasenburg, J., & Bermbach, D. (2020). Towards Geo-Context Aware IoT Data Distribution. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12019 LNCS, pp. 111–121). Springer. https://doi.org/10.1007/978-3-030-45989-5_9
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