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Toward heterogeneous computing to facilitate sequential OLAP real-time applications

Over the last decade, due to the need of analyzing and studying the logical order that data exhibit in various industries, sequential data storage and processing field has attracted a significant number of researchers. Recently, sequential OLAP has emerged as one of sequential data subfields wh...

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Main Authors: Hameed, Shihab A., Habaebi, Mohamed Hadi, Alzeini, Haytham I. M.
Format: Conference or Workshop Item
Language:English
English
Published: IEEE 2016
Subjects:
T Technology (General)
T58.5 Information technology
Online Access:http://irep.iium.edu.my/54579/8/54579.pdf
http://irep.iium.edu.my/54579/9/54579-Toward%20Heterogeneous%20Computing%20to%20Facilitate%20Sequential%20OLAP%20Real-Time%20Applications_SCOPUS.pdf
http://irep.iium.edu.my/54579/
http://ieeexplore.ieee.org/document/7808320/
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spelling my.iium.irep.545792017-05-23T08:19:39Z http://irep.iium.edu.my/54579/ Toward heterogeneous computing to facilitate sequential OLAP real-time applications Hameed, Shihab A. Habaebi, Mohamed Hadi Alzeini, Haytham I. M. T Technology (General) T58.5 Information technology Over the last decade, due to the need of analyzing and studying the logical order that data exhibit in various industries, sequential data storage and processing field has attracted a significant number of researchers. Recently, sequential OLAP has emerged as one of sequential data subfields whereby traditional OLAP - which mainly utilizes a set data-based analysis, do not satisfy the hunger of performing pattern-based operations and time-based analysis. Such analyses can provide an insightful perspective and reveal hidden correlations among events patterns through time. Therefore, extended query languages, new OLAP cube models and optimized algorithms and infrastructures have been introduced. However, the ever grown data size has always been deemed a major hurdle in the way of fully taking advantage of this data. In this context, and based on our proposed optimized heterogeneous Rabin-Karp algorithm earlier, we suggest a high performance sequential pattern detection approach that works in harmony Sequential OLAP processing requirements. The optimized algorithm is dedicated to detect patterns over parallel data streams in Real-Time. The empirical results have shown more than ten times speedup over the multi-core version. IEEE 2016 Conference or Workshop Item REM application/pdf en http://irep.iium.edu.my/54579/8/54579.pdf application/pdf en http://irep.iium.edu.my/54579/9/54579-Toward%20Heterogeneous%20Computing%20to%20Facilitate%20Sequential%20OLAP%20Real-Time%20Applications_SCOPUS.pdf Hameed, Shihab A. and Habaebi, Mohamed Hadi and Alzeini, Haytham I. M. (2016) Toward heterogeneous computing to facilitate sequential OLAP real-time applications. In: 6th International Conference on Computer and Communication Engineering (ICCCE 2016), 25th-27th July 2016, Kuala Lumpur. http://ieeexplore.ieee.org/document/7808320/ 10.1109/ICCCE.2016.62
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
topic T Technology (General)
T58.5 Information technology
spellingShingle T Technology (General)
T58.5 Information technology
Hameed, Shihab A.
Habaebi, Mohamed Hadi
Alzeini, Haytham I. M.
Toward heterogeneous computing to facilitate sequential OLAP real-time applications
description Over the last decade, due to the need of analyzing and studying the logical order that data exhibit in various industries, sequential data storage and processing field has attracted a significant number of researchers. Recently, sequential OLAP has emerged as one of sequential data subfields whereby traditional OLAP - which mainly utilizes a set data-based analysis, do not satisfy the hunger of performing pattern-based operations and time-based analysis. Such analyses can provide an insightful perspective and reveal hidden correlations among events patterns through time. Therefore, extended query languages, new OLAP cube models and optimized algorithms and infrastructures have been introduced. However, the ever grown data size has always been deemed a major hurdle in the way of fully taking advantage of this data. In this context, and based on our proposed optimized heterogeneous Rabin-Karp algorithm earlier, we suggest a high performance sequential pattern detection approach that works in harmony Sequential OLAP processing requirements. The optimized algorithm is dedicated to detect patterns over parallel data streams in Real-Time. The empirical results have shown more than ten times speedup over the multi-core version.
format Conference or Workshop Item
author Hameed, Shihab A.
Habaebi, Mohamed Hadi
Alzeini, Haytham I. M.
author_facet Hameed, Shihab A.
Habaebi, Mohamed Hadi
Alzeini, Haytham I. M.
author_sort Hameed, Shihab A.
title Toward heterogeneous computing to facilitate sequential OLAP real-time applications
title_short Toward heterogeneous computing to facilitate sequential OLAP real-time applications
title_full Toward heterogeneous computing to facilitate sequential OLAP real-time applications
title_fullStr Toward heterogeneous computing to facilitate sequential OLAP real-time applications
title_full_unstemmed Toward heterogeneous computing to facilitate sequential OLAP real-time applications
title_sort toward heterogeneous computing to facilitate sequential olap real-time applications
publisher IEEE
publishDate 2016
url http://irep.iium.edu.my/54579/8/54579.pdf
http://irep.iium.edu.my/54579/9/54579-Toward%20Heterogeneous%20Computing%20to%20Facilitate%20Sequential%20OLAP%20Real-Time%20Applications_SCOPUS.pdf
http://irep.iium.edu.my/54579/
http://ieeexplore.ieee.org/document/7808320/
_version_ 1643614580198342656
score 13.211869

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