BIRS Workshop Lecture Videos

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BIRS Workshop Lecture Videos

Big Data and Small Devices Morik, Katharina


Big data are produced by various sources. Most often, they are distributedly stored at computing farms or clouds. Analytics on the Hadoop Distributed File System (HDFS) then follows the MapReduce programming model (batch layer). It is complemented by the speed layer, which aggregates and integrates incoming data streams in real time. When considering big data and small devices, obviously, we imagine the small devices being hosts of the speed layer, only. Analytics on the small devices is restricted by memory and computation resources. The interplay of streaming and batch analytics offers a multitude of configurations. The collaborative research center SFB 876 investigates data analytics for and on small devices regarding runtime, memory and energy consumption. In this talk, we investigate graphical models, which generate the probabilities for connected (sensor) nodes. Resource-restricted methods deliver insights fast enough for a more interactive analysis.

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