Title: On the convergence and optimality of the firefly algorithm for opportunistic spectrum access

Authors: Lakshmana Rao Kalabarige; Sireesha Rodda; Shanti Chilukuri

Addresses: Department of Computer Science and Engineering, GMR Institute of Technology, Rajam, India ' Department of Computer Science and Engineering, GITAM Institute of Technology, GITAM University, Visakhapatnam, India ' Department of Computer Science and Engineering, GVP College of Engineering (A), Visakhapatnam, India

Abstract: Meta-heuristic algorithms have been proven to be efficient for engineering optimisation. However, the convergence and accuracy of such algorithms depends on the objective function and also on several choices made during algorithm design. In this paper, we focus on the firefly algorithm for optimal channel allocation in cognitive radio networks. We study the effect of various probability distributions including the Lévy alpha stable distribution for randomisation of firefly movement. We also explore various functions for converting firefly positions from the continuous space to the discrete space, as is necessary in the spectrum allocation problem. Simulation results show that in most cases, Lévy flight gives better convergence time and results for common optimisation problems such as maximising the overall channel utilisation, maximising the channel allocation for the bottleneck user and maximising proportional fairness. We also note that no single discretisation function gives both good convergence and optimality.

Keywords: meta-heuristic algorithms; Lévy flight; spectrum allocation; cognitive radio networks; firefly algorithm; optimality; convergence; randomisation; channel utilisation; proportional fairness.

DOI: 10.1504/IJAIP.2021.112900

International Journal of Advanced Intelligence Paradigms, 2021 Vol.18 No.2, pp.119 - 133

Received: 13 Mar 2017
Accepted: 28 Oct 2017

Published online: 09 Feb 2021 *

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