A Method for Compressing Event Log Data Based on Combinatorial Generation Using AND/OR Tree Structures

The exponential growth in the volume of digital information produced by modern society entails the problem of storing large amounts of data, including archival data. Archival data refers to the category of “cold” data (data that requires storage, but is rarely used). A clear example of this type of...

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Main Author: Yuriy Shablya
Format: Article
Language:Russian
Published: The Fund for Promotion of Internet media, IT education, human development «League Internet Media» 2023-10-01
Series:Современные информационные технологии и IT-образование
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Online Access:http://sitito.cs.msu.ru/index.php/SITITO/article/view/988
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author Yuriy Shablya
author_facet Yuriy Shablya
author_sort Yuriy Shablya
collection DOAJ
description The exponential growth in the volume of digital information produced by modern society entails the problem of storing large amounts of data, including archival data. Archival data refers to the category of “cold” data (data that requires storage, but is rarely used). A clear example of this type of archival data is data from event logs, which contain a brief description of events that occurred in the information system in chronological order. Due to the large amount of archival data and its rare use, it is relevant to store such data in compressed form. This article discusses the problem of developing a method for compressing archival data using the example of event log data by applying combinatorial generation algorithms. In particular, if we fix some current state of the event log, then the set of its entries can be considered as a combinatorial set. Then, using an algorithm for ranking elements of the combinatorial set, each event log entry can be encoded with a single number, which will require less memory to store. Based on this idea, a method for compressing event log data based on combinatorial generation using AND/OR tree structures is proposed. To evaluate the effectiveness of the proposed method, an example of compressing event log data generated within Moodle electronic courses is considered. The results of the experimental study confirmed the effectiveness of the proposed method: the total amount of memory required to store the event log of a Moodle electronic course in the compressed form is less compared to the existing methods for compressing text files.
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institution OA Journals
issn 2411-1473
language Russian
publishDate 2023-10-01
publisher The Fund for Promotion of Internet media, IT education, human development «League Internet Media»
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series Современные информационные технологии и IT-образование
spelling doaj-art-948cb0a84d4f4205a98dc0121feeb7662025-08-20T01:55:49ZrusThe Fund for Promotion of Internet media, IT education, human development «League Internet Media»Современные информационные технологии и IT-образование2411-14732023-10-0119356457410.25559/SITITO.019.202303.564-574A Method for Compressing Event Log Data Based on Combinatorial Generation Using AND/OR Tree StructuresYuriy Shablya0https://orcid.org/0000-0002-9695-7493Tomsk State University of Control Systems and Radioelectronics, Tomsk, RussiaThe exponential growth in the volume of digital information produced by modern society entails the problem of storing large amounts of data, including archival data. Archival data refers to the category of “cold” data (data that requires storage, but is rarely used). A clear example of this type of archival data is data from event logs, which contain a brief description of events that occurred in the information system in chronological order. Due to the large amount of archival data and its rare use, it is relevant to store such data in compressed form. This article discusses the problem of developing a method for compressing archival data using the example of event log data by applying combinatorial generation algorithms. In particular, if we fix some current state of the event log, then the set of its entries can be considered as a combinatorial set. Then, using an algorithm for ranking elements of the combinatorial set, each event log entry can be encoded with a single number, which will require less memory to store. Based on this idea, a method for compressing event log data based on combinatorial generation using AND/OR tree structures is proposed. To evaluate the effectiveness of the proposed method, an example of compressing event log data generated within Moodle electronic courses is considered. The results of the experimental study confirmed the effectiveness of the proposed method: the total amount of memory required to store the event log of a Moodle electronic course in the compressed form is less compared to the existing methods for compressing text files.http://sitito.cs.msu.ru/index.php/SITITO/article/view/988combinatorial generationevent logdata compressionand/or treeranking algorithm
spellingShingle Yuriy Shablya
A Method for Compressing Event Log Data Based on Combinatorial Generation Using AND/OR Tree Structures
Современные информационные технологии и IT-образование
combinatorial generation
event log
data compression
and/or tree
ranking algorithm
title A Method for Compressing Event Log Data Based on Combinatorial Generation Using AND/OR Tree Structures
title_full A Method for Compressing Event Log Data Based on Combinatorial Generation Using AND/OR Tree Structures
title_fullStr A Method for Compressing Event Log Data Based on Combinatorial Generation Using AND/OR Tree Structures
title_full_unstemmed A Method for Compressing Event Log Data Based on Combinatorial Generation Using AND/OR Tree Structures
title_short A Method for Compressing Event Log Data Based on Combinatorial Generation Using AND/OR Tree Structures
title_sort method for compressing event log data based on combinatorial generation using and or tree structures
topic combinatorial generation
event log
data compression
and/or tree
ranking algorithm
url http://sitito.cs.msu.ru/index.php/SITITO/article/view/988
work_keys_str_mv AT yuriyshablya amethodforcompressingeventlogdatabasedoncombinatorialgenerationusingandortreestructures
AT yuriyshablya methodforcompressingeventlogdatabasedoncombinatorialgenerationusingandortreestructures