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Divisible load scheduling of image processing applications on the heterogeneous star and tree networks using a new genetic algorithm
Author(s) -
Nikbakht Aali Sahar,
Bagherzadeh Nader
Publication year - 2019
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.5498
Subject(s) - computer science , parallel computing , computation , scheduling (production processes) , image processing , algorithm , kernel (algebra) , star (game theory) , tree (set theory) , image (mathematics) , load balancing (electrical power) , distributed computing , mathematical optimization , mathematics , artificial intelligence , mathematical analysis , geometry , combinatorics , grid
Summary The divisible load scheduling of image processing applications on the heterogeneous star and multi‐level tree networks is addressed in this paper. In our platforms, processors and network links have different speeds. In addition, computation and communication overheads are considered. A new genetic algorithm for minimizing the processing time of low‐level image applications using divisible load theory is introduced. The closed‐form solution for the processing time, the image fractions that should be allocated to each processor, the optimum number of participating processors, and the optimal sequence for load distribution are derived. The new concept of equivalent processor in tree network is introduced and the effect of different image and kernel sizes on processing time and speed up are investigated. Finally, to indicate the efficiency of our algorithm, several numerical experiments are presented.