Sentence examples for data stream processing from inspiring English sources
To do so, we first modeled and performed an intrinsic evaluation to assess the performance of three outlier detection algorithms formulated as a data stream processing network which receives as input and processes data streams of smartphone and vehicle sensors.
Data stream processing is a computational paradigm that aims at addressing this challenge by processing data streams in an on-the-fly manner, in contrast to the more traditional and less efficient store-and-then process approach.
In many systems, such as data stream processing ones, the components have indirect dependencies.
Fig. 4 Overview of the mobile-cloud system for data stream processing.
Thus, during the data stream processing, we had 17.5 times more evidence of acceleration than speed.
Large community driven projects have developed frameworks optimized for distributed data stream processing.
The same process is impossible in data streams processing.
Bayesian learning provides a firm theoretical basis of the design and exploitation of algorithms in data-streams processing (preprocessing, change detection, hypothesis testing, clustering, etc).. Primarily, it relies on a recursive parameter estimation of a firmly bounded complexity.
In the "Data processing engines" section, we discuss the differences between batch processing, which works on historical data, and stream processing, which analyzes the data in real-time as it is generated.
We organize related work in three categories: "Processing streams of data" overviews the main approaches and systems to process streams of dynamic data, "Modeling stream processing" presents contributions that target the modeling of stream processing systems, and "Windowing approaches" discusses some proposals for windowing approaches that go beyond those captured by SECRET.
In other words, the Flow platform enables developers to take advantage of a ready-to-use backend for app data (including stream processing and aggregation) in the hopes of increasing efficiency and lowering the cost of implementing realtime data systems for their apps.
