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Direct Analytics of Generalized Deduplication Compressed IoT Data

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Given the ever increasing volume of data generated by the Internet of Things, data compression plays an essential role in reducing the cost of data transmission and storage. However, it also introduces a barrier, namely decompression, between users and the data-driven insights they require. We propose techniques for direct analytics of compressed data based on the Generalised Deduplication compression algorithm. When applied to data clustering, the accuracy of the proposed method differs by merely 1-5% when compared to analytics performed upon the uncompressed data. However, it runs four times faster, accesses only 14% as much data and, since the data is always compressed, requires significantly less storage. These results show that it is possible to simultaneously reap the benefits of compression and accurate, high-speed analytics in many applications.
OriginalsprogEngelsk
TitelIEEE Global Communications Conference
ForlagIEEE
StatusAccepteret/In press - 2021
SerietitelGlobecom. I E E E Conference and Exhibition
ISSN1930-529X

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