SOLVING SAT IN A DISTRIBUTED CLOUD: A PORTFOLIO APPROACH - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue International Journal of Applied Mathematics and Computer Science Année : 2019

SOLVING SAT IN A DISTRIBUTED CLOUD: A PORTFOLIO APPROACH

Résumé

We introduce a new parallel and distributed algorithm for the solution of the satisfiability problem. It is based on an algorithm portfolio and is intended to be used for servicing requests in a distributed cloud. The core of our contribution is the modeling of the optimal resource sharing schedule in parallel executions and the proposition of heuristics for its approximation. For this purpose, we reformulate a computational problem introduced in a prior work. The main assumption is that it is possible to learn optimal resource sharing from traces collected on past executions on a representative set of instances. We show that the learning can be formalized as a set coverage problem. Then we propose to solve it by approximation and dynamic programming algorithms based on classical greedy algorithms for the maximum coverage problem. Finally, we conduct an experimental evaluation for comparing the performance of the various algorithms proposed. The results show that some algorithms become more competitive if we intend to determine the trade-off between their quality and the runtime required for their computation.
Fichier principal
Vignette du fichier
AMCS_2019_29_2_4.pdf (364.56 Ko) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte
Loading...

Dates et versions

hal-02443995 , version 1 (17-01-2020)

Identifiants

Citer

Yanik Ngoko, Christophe Cérin, Denis Trystram. SOLVING SAT IN A DISTRIBUTED CLOUD: A PORTFOLIO APPROACH. International Journal of Applied Mathematics and Computer Science, 2019, 29 (2), pp.261 - 274. ⟨10.2478/amcs-2019-0019⟩. ⟨hal-02443995⟩
67 Consultations
188 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More