TREAT - Two wRongs makE A righT: efficient distributed storage and queries of IoT datasets with erasure coding and compression Article Swipe
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· 2024
· Open Access
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· DOI: https://doi.org/10.1145/3629104.3666039
· OA: W4400880340
Erasure coding in distributed multi-cloud data storage increases availability, durability and security, but it also makes data analytics inefficient since the whole dataset must be reconstructed to answer a query, even if the result set is a small fraction of the complete file. Data compression has a similar trade-off as it can reduce storage costs while requiring the entire compressed data to be collected and decompressed in order to access even a few bytes. We propose TREAT, a novel method that combines erasure coding and compression to achieve efficient queries of time series datasets while keeping the benefits of both underlying techniques. Our evaluation of five real-life datasets shows that it can answer range queries up to 25 times faster with 100 times less data transfer than reconstructing the whole dataset.
