Smart Meter Data Compression using Generalized Deduplication

被引：5

作者：

Feher, Marcell ^{[1
]}

Yazdani, Niloofar ^{[1
]}

Hansen, Morten Tranberg ^{[2
]}

Vester, Flemming Enevold ^{[2
]}

Lucani, Daniel E. ^{[1
]}

机构：

[1] Aarhus Univ, Agile Cloud Lab, DIGIT, Aarhus, Denmark

[2] Kamstrup AS, Skanderborg, Denmark

来源：

2020 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM) | 2020年

关键词：

compression; IoT; generalized deduplication; smart meters;

D O I：

10.1109/GLOBECOM42002.2020.9322393

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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 arc 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.

引用

页数：6

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