Parallel Differential Evolution approach for Cloud workflow placements under simultaneous optimization of multiple objectives - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2016

Parallel Differential Evolution approach for Cloud workflow placements under simultaneous optimization of multiple objectives

Résumé

The recent rapid expansion of Cloud computing facilities triggers an attendant challenge to facility providers and users for methods for optimal placement of workflows on distributed resources, under the often-contradictory impulses of minimizing makespan, energy consumption, and other metrics. Evolutionary Optimization techniques that from theoretical principles are guaranteed to provide globally optimum solutions, are among the most powerful tools to achieve such optimal placements. Multi-Objective Evolutionary algorithms by design work upon contradictory objectives, gradually evolving across generations towards a converged Pareto front representing optimal decision variables – in this case the mapping of tasks to resources on clusters. However the computation time taken by such algorithms for convergence makes them prohibitive for real time placements because of the adverse impact on makespan. This work describes parallelization, on the same cluster, of a Multi-Objective Differential Evolution method (NSDE-2) for optimization of workflow placement, and the attendant speedups that bring the implicit accuracy of the method into the realm of practical utility. Experimental validation is performed on a real-life testbed using diverse Cloud traces. The solutions under different scheduling policies demonstrate significant reduction in energy consumption with some improvement in makespan.
Fichier principal
Vignette du fichier
CEC2016.pdf (430.78 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01289176 , version 1 (26-05-2016)
hal-01289176 , version 2 (10-06-2016)

Identifiants

  • HAL Id : hal-01289176 , version 2

Citer

Daniel Balouek-Thomert, Arya K. Bhattacharya, Eddy Caron, Karunakar Gadireddy, Laurent Lefèvre. Parallel Differential Evolution approach for Cloud workflow placements under simultaneous optimization of multiple objectives. Congress on Evolutionary Computation (IEEE CEC 2016), Jul 2016, Vancouver, Canada. ⟨hal-01289176v2⟩
621 Consultations
345 Téléchargements

Partager

Gmail Facebook X LinkedIn More