Swinging door alogrithm

Duration: 4min 15sec Views: 202 Submitted: 03.09.2020
Category: Casting
In Internet of Things IoT scenarios where monitoring and sensors are involved, data is constantly generated over time in streaming applications with large or even extreme amounts of data is recorded. For example, in performance monitoring scenarios, a curve that indicates performance is drawn based on several data points that are collected and recorded over time. These sorts of applications are now common in several industries nowadays, especially the IT, medicine, and finance sectors. Now, imagine that if each sensor or metric involved in these IoT applications generates 1 point every milliseconds, which in turn means that , points are generated on a daily basis. Now consider that there are several, or even several thousand or even millions of, sensors or metrics involved in such an application.

GitHub - gfoidl/DataCompression: Data compression -- Swinging Door Algorithm

Skip to Main Content. A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. Use of this web site signifies your agreement to the terms and conditions. Thus, the compressed data becomes a subset of the raw PMU measurements.

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