Big data compression using spiht in Hadoop: A case study in multi-lead ECG signals

Grafika Jati, Ilham Kusuma, M. H. Hilman, Wisnu Jatmiko

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Compression still become main concern in big data framework. The performance of big data depend on speed of data transfer. Compressed data can speed up transfer data between network. It also save more space for storage. Several compression method is provide by Hadoop as a most common big data framework. That method mostly for general purpose. But the performance still have to optimize especially for Biomedical record like ECG data. We propose Set Partitioning in Hierarchical Tree (SPIHT) for big data compression with study case ECG signal data. In this paper compression will run in Hadoop Framework. The proposed method has stages such as input signal, map input signal, spiht coding, and reduce bit-stream. The compression produce compressed data for intermediate (Map) output and final (reduce) output. The experiment using ECG data to measure compression performance. The proposed method gets Percentage Root-mean-square difference (PRD) is about 1.0. Compare to existing method, the proposed method get better Compression Ratio (CR) with competitive longer compression time. So proposed method gets better performance compare to other method especially for ECG dataset.

Original languageEnglish
Title of host publication2016 International Workshop on Big Data and Information Security, IWBIS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages133-137
Number of pages5
ISBN (Electronic)9781509034772
DOIs
Publication statusPublished - 6 Mar 2017
Event2016 International Workshop on Big Data and Information Security, IWBIS 2016 - Jakarta, Indonesia
Duration: 18 Oct 201619 Oct 2016

Publication series

Name2016 International Workshop on Big Data and Information Security, IWBIS 2016

Conference

Conference2016 International Workshop on Big Data and Information Security, IWBIS 2016
Country/TerritoryIndonesia
CityJakarta
Period18/10/1619/10/16

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