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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iium-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 PeerReviewed 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 |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
International Islamic University Malaysia |
| building |
IIUM Repository |
| collection |
Online Access |
| 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/ http://irep.iium.edu.my/54579/ http://irep.iium.edu.my/54579/ 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 |
| first_indexed |
2023-09-18T21:17:13Z |
| last_indexed |
2023-09-18T21:17:13Z |
| _version_ |
1777411642544357376 |