Abstract
The growing usage of the industrial cognitive radio sensor network (ICRSN) brings profound changes to the Internet of Things. The ICRSN is an emerging technique to transfer industrial data, which has strict and accurate communication requirements in a large number of areas such as environmental surveillance, building monitoring, control, and many other areas. The problem of maximizing the sum bandwidth by using a spectrum allocation algorithm has been extensively studied in this paper. Inspired by chaos theory and quantum computing, this work presents a new chaotic hybrid immune genetic algorithm (CHIGA). We then introduce a spectrum allocation model that considers both network reward, throughput, and convergence time. The improvement of CHIGA performance through experimental simulations is evaluated in terms of the sum network reward compared to methods based on simulated annealing (SA), ant colony optimization (ACO), and particle swarm optimization (PSO). Simulation results show that the CHIGA has a higher network reward and throughput existing optimized algorithms while maintaining total system throughput.
Highlights
In the past decades, information and communication technology is developing rapidly
The reward and throughput of the chaotic hybrid immune genetic algorithm (CHIGA) are analyzed and tested. We compare it against the ant colony optimization (ACO), simulated annealing (SA), and particle swarm optimization (PSO) for the problem of maximizing the network reward using spectrum allocation
All comparisons between CHIGA, ACO, PSO, and SA were reported using the same number of iterations and population size
Summary
Information and communication technology is developing rapidly. Industrial wireless technology has become a new research hotspot in the field of industrial control [1, 2]. A considerable number of frequency bands are not fully utilized. The currently adopted spectrum allocation strategy has caused some frequency bands to be crowded, while other frequency bands are extremely low. The problems of wireless spectrum resource shortage and spectrum utilization unevenness are studied. The research is focusing on developing new spectrum allocation schemes to maximize the network reward and improve the throughput in industrial cognitive radio sensor networks (ICRSNs) [3]
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