Log files provide valuable insight to previous history of system's usages. Using the information from a log file can help improve future access of a system. However, log files often contain huge amount of data whi...
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Log files provide valuable insight to previous history of system's usages. Using the information from a log file can help improve future access of a system. However, log files often contain huge amount of data which require significant amount of time to be processed. Even though some popular algorithms already exist to handle this, it is still an open challenge for researchers to further improve them. Hence, in this paper, a novel binary-based approach for frequency mining of a database log file is presented. The approach includes the use of a new algorithms along with its supportive data structures. Construction of the approach began with evaluation of some of the existing methods and identifying their drawbacks. From there the new algorithms were developed and tested. Initial experimentation of the approach reveals a significant improvement in terms of the execution time of the log file's frequency mining calculation.
This paper shows an effective all-reduction algorithm and its implementation on the Message Passing Interface. It performs comparatively stable in case not only composite numbers of processors but also prime numbers, ...
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ISBN:
(纸本)9780889866379
This paper shows an effective all-reduction algorithm and its implementation on the Message Passing Interface. It performs comparatively stable in case not only composite numbers of processors but also prime numbers, since we introduce the process detachment strategy on each factorizing stage. On a preliminary test, we examine its efficiency, and we discuss and compare it with the existing algorithms by introducing a performance model of our algorithm.
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