A Scalable Smart Meter Data Generator Using Spark

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Today, smart meters are being used worldwide. As a matter of fact smart meters produce large volumes of data. Thus, it is important for smart meter data management and analytics systems to process petabytes of data. Benchmarking and testing of these systems require scalable data, however, it can be challenging to get large data sets due to privacy and/or data protection regulations. This paper presents a scalable smart meter data generator using Spark that can generate realistic data sets. The proposed data generator is based on a supervised machine learning method that can generate data of any size by using small data sets as seed. Moreover, the generator can preserve the characteristics of data with respect to consumption patterns and user groups. This paper evaluates the proposed data generator in a cluster based environment in order to validate its effectiveness and scalability.
Original languageEnglish
Title of host publicationOTM Confederated International Conferences "On the Move to Meaningful Internet Systems"
PublisherSpringer
Publication date2017
Pages21-36
DOIs
Publication statusPublished - 2017
EventOn the Move to Meaningful Internet Systems. OTM 2017 - Rhodos, Greece
Duration: 23 Oct 201727 Oct 2017

Conference

ConferenceOn the Move to Meaningful Internet Systems. OTM 2017
CountryGreece
CityRhodos
Period23/10/201727/10/2017
SeriesLecture Notes in Computer Science
Volume10573
ISSN0302-9743
CitationsWeb of Science® Times Cited: No match on DOI

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