Title: A Pareto optimal multi-objective optimisation for parallel dynamic programming algorithm applied in cognitive radio ad hoc networks

Authors: Badr Benmammar; Youcef Benmouna; Francine Krief

Addresses: LTT Laboratory, University of Tlemcen, Tlemcen, Algeria ' LTT Laboratory, University of Tlemcen, Tlemcen, Algeria ' LaBRI Laboratory, Bordeaux INP, Talence, France

Abstract: In this paper, we present a Pareto optimal multi-objective optimisation for parallel dynamic programming algorithm applied in cognitive radio ad hoc networks. To measure the performance of our contribution, we have used a multi-core architecture. The parallel version of the dynamic programming is implemented with the concept of Pareto. To select the most compromising solution from the Pareto front, Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is used in this paper. We have also implemented a meta-heuristic (cuckoo search) with the Pareto principle in order to validate our proposal. Our simulations approve the desired results, showing significant gain in terms of execution time. The main objective is to allow a cognitive engine to use an exact method and to have better results compared to the use of meta-heuristics while satisfying QoS parameters.

Keywords: Pareto; multi-objective optimisation; QoS; parallel computing; dynamic programming; cuckoo search.

DOI: 10.1504/IJCAT.2019.098036

International Journal of Computer Applications in Technology, 2019 Vol.59 No.2, pp.152 - 164

Received: 05 Mar 2018
Accepted: 06 May 2018
Published online: 27 Feb 2019 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article