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

摘要

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.