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Smart Meter Data Compression using Generalized Deduplication

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

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  • 1570643131

    Accepted manuscript, 570 KB, PDF document

DOI

Utility providers are relying more often on smart, wirelessly connected smart meters to collect consumption information of their customers. The sheer amount of connected smart meters and the growing requirements to provide more frequent reports from each device are putting a large strain on existing systems and protocols. In this paper, we propose three novel lossless compression schemes that significantly reduce the size of standard DLMS data messages uploaded by smart electricity meters. Using real life data sets, we show that these methods can achieve compression rates of over 90% while being transparent to the DLMS protocol and eliminating the privacy concerns of the existing compression methods.
Original languageEnglish
Title of host publicationGLOBECOM 2020 - 2020 IEEE Global Communications Conference : Proceedings
Number of pages6
PublisherIEEE
Publication year2020
ISBN (Electronic)978-1-7281-8298-8
DOIs
Publication statusPublished - 2020
Event2020 IEEE Global Communications Conference - Taipei, Taiwan + Online (Hybrid), Taipei, Taiwan
Duration: 7 Dec 202011 Dec 2020
https://globecom2020.ieee-globecom.org/

Conference

Conference2020 IEEE Global Communications Conference
LocationTaipei, Taiwan + Online (Hybrid)
LandTaiwan
ByTaipei
Periode07/12/202011/12/2020
Internetadresse

    Research areas

  • generalized deduplication, Compression, IoT, Smart meters

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