CROSS-LAYER PARAMETERS RECONFIGURATION IN INDUSTRIAL COGNITIVE WIRELESS NETWORKS USING MOABCHV ALGORITHM

Xiaojian You, Xiaohai He, Xuemei Han, Chun Wu, and Hong Jiang

Keywords

Industrial cognitive wireless networks, crosslayer cognitive decision engine, highdimensional multiobjective optimization, multiobjective artificial bee colony algorithm based on hypervolume,fuzzy decisionmaking

Abstract

To solve parameters reconfiguration issue of industrial cognitive wireless networks, a cross-layer cognitive decision engine based on the hyper-volume multi-objective artificial bee colony algorithm (MOABChv) and fuzzy decision-making is proposed. The overall network performance optimization is modelled as a high-dimensional multi-objective optimization problem. The hyper-volume indices are introduced to judge the merits of high-dimensional target solutions. The integration of cellular automata and social cognitive strategies accelerates the convergence of the algorithm. Fuzzy decisionmaking technology is adopted to choose the optimal solution that meets the user needs. Simulation results show that the proposed MOABChv algorithm could solve a high-dimensional multi-objective optimization problem, its performance is better than NSGA2 and MOABC algorithms. The proposed cognitive decision engine can effectively achieve the multi-objective and multi-parameter crosslayer optimization reconfiguration.

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