Springer Nature
SymED-artifact.zip (56.16 MB)

Artifact and instructions to generate experimental results for Euro-Par 2023 paper: SymED: Adaptive and Online Symbolic Representation of Data on the Edge

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posted on 2024-05-15, 09:50 authored by Daniel Hofstätter, Shashikant Ilager, Ivan Lujic, Ivona Brandic

This artifact generates figures and tables for SymED (Symbolic Representation of Data on the Edge). SymED takes the ABBA (Adaptive Brownian Bridge-based symbolic Aggregation of time series) algorithm and extends it to be online, adaptive and distributed. The sender side does intial compression for a given data stream, and sends the compressed data to the receiver. The receiver converts the data to a symbolic representation, one symbol at a time. Symbols can be reconstructed to a time series again, with controllable error. Evaluation is done on the UCR Time Series Classification Archive. Instructions on how to reproduce the results can be found in the OverviewDocument.pdf, as well as in the README.md.


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