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Publication type: Conference paper
Type of review: Peer review (publication)
Title: Comparison and model of compression techniques for smart cloud log file handling
Authors: Spillner, Josef
et. al: No
DOI: 10.1109/CCCI49893.2020.9256609
Proceedings: 2020 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI)
Page(s): 1
Pages to: 6
Conference details: International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI), Sharjah, UAE (online), 3-5 November 2020
Issue Date: 5-Nov-2020
Publisher / Ed. Institution: IEEE
ISBN: 978-1-7281-7315-3
Language: English
Subjects: Log file management; Compression algorithm; Text compression; Benchmark; Adaptivity; Smart system
Subject (DDC): 004: Computer science
Abstract: Compression as data coding technique has seen approximately 70 years of research and practical innovation. Nowadays, powerful compression tools with good trade-offs exist for a range of file formats from plain text to rich multimedia. Yet in the dilemma of cloud providers to reduce log data sizes as much as possible while having to keep as much as possible around for regulatory reasons and compliance processes, many companies are looking for smarter solutions beyond brute compression. In this paper, comprehensive applied research setting around network and system logs is introduced by comparing text compression ratios and performance. The benchmark encompasses 13 tools and 30 tool-configuration-search combinations. The tool and algorithm relationships as well as benchmark results are modelled in a graph. After discussing the results, the paper reasons about limitations of individual approaches and suitable combinations of compression with smart adaptive log file handling. The adaptivity is based on the exploitation of knowledge on format-specific compression characteristics expressed in the graph, for which a proof-of-concept advisor service is provided.
Fulltext version: Accepted version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Organisational Unit: Institute of Applied Information Technology (InIT)
Published as part of the ZHAW project: Application of stealth computing in highly information-sensitive cloud environments
Appears in collections:Publikationen School of Engineering

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