Open AccessPARTITIONING AND SCHEDULING RESOLUTION PROBLEMS BY BEES MATING STRATEGY IN DRES’ SYSTEMS
Author(s) -
Khadidja Yahyaoui
Publication year - 2017
Publication title -
computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.184
H-Index - 11
eISSN - 2312-5381
pISSN - 1727-6209
DOI - 10.47839/ijc.16.2.886
Subject(s) - computer science , tabu search , metaheuristic , simulated annealing , scheduling (production processes) , bees algorithm , mathematical optimization , software , algorithm , mathematics , programming language
In last years, several approaches have been proposed for solving the Hardware/Software partitioning and scheduling problem in dynamically reconfigurable embedded systems (DRESs), directed by metaheuristic algorithms. Honey Bees Mating Optimization (HBMO) algorithm is one of these advanced methods. It is a nature inspired algorithm which simulates the process of real honey-bees mating. In this work, we propose a variant of the Honey-bee Mating Optimization Algorithm for solving Hardware/software (HW/SW) partitioning and scheduling problems in DRESs. The algorithm is used in a hybrid scheme with other metaheuristic algorithms for successfully solving these problems. More precisely, the proposed algorithm (HBMO_ DRESs) combines a Honey Bees Mating Optimization (HBMO) algorithm, the Tabu Search (TS) and Simulated Annealing (SA)). From an acyclic task graph and a set of Area-Time implementation trade off points for each task, the adopted method performs HW/SW partitioning and scheduling such that the global application execution time is minimized. Comparing the proposed method with Genetic Algorithm and Evolutionary Strategies (ES), the simulation results show that the proposed algorithm has better convergence performance.