Practical Implementation of M4 for Web Visualization Service.

Vast volumes of time series are becoming more common in part to recent research advancements in big data analytics and sensor/ monitoring networks. However, tranmission of time series for visualization services can cause serious bandwidth wastage and extensive network delays if there is no efficient data management. Existing work such as M4 aim to solve this problem by providing high data reduction rates through data aggregation and guaranteeing the reliability of visualization results at the same time. However, current work on M4 does not consider verification in a more practical environment; for example experimentation on web-based servers that are openly accessible by users. In this paper, we propose inter-pixel gradient-based M4 (IGM4) for enhancing the existing M4 scheme, and conduct a study to reduce the amount of data and delay without distorting the results of visualized graph. We build user-friendly web-based system to dealing with the data processing technique, and perform test on the empirical environment. Finally, we present the results of performance evaluation through comparison among the original data, M4, and IGM4 reflecting the various kinds of time series and resolutions.