An Efficient Pareto Optimal Resource Allocation Scheme in Cognitive Radio-Based Internet of Things Networks

The high data rates detail that internet-connected devices have been increasing exponentially. Cognitive radio (CR) is an auspicious technology used to address the resource shortage issue in wireless IoT networks. Resource optimization is considered a non-convex and nondeterministic polynomial (NP)...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2022-01, Vol.22 (2), p.451
Main Authors: Latif, Shahzad, Akraam, Suhail, Karamat, Tehmina, Khan, Muhammad Attique, Altrjman, Chadi, Mey, Senghour, Nam, Yunyoung
Format: Article
Language:English
Subjects:
Algorithms
Cognitive radio
Communication
CR-IoT networks
Data transmission
Efficiency
Energy
Energy efficiency
Heuristic
Internet
Internet of Things
Linear programming
Objectives
Optimization algorithms
Pareto efficiency
pareto optimality
Polynomials
Receivers & amplifiers
Resource allocation
spectral efficiency
Spectrum allocation
Tabu search
Transmitters
Wireless networks
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Summary:The high data rates detail that internet-connected devices have been increasing exponentially. Cognitive radio (CR) is an auspicious technology used to address the resource shortage issue in wireless IoT networks. Resource optimization is considered a non-convex and nondeterministic polynomial (NP) complete problem within CR-based Internet of Things (IoT) networks (CR-IoT). Moreover, the combined optimization of conflicting objectives is a challenging issue in CR-IoT networks. In this paper, energy efficiency (EE) and spectral efficiency (SE) are considered as conflicting optimization objectives. This research work proposed a hybrid tabu search-based stimulated algorithm (HTSA) in order to achieve Pareto optimality between EE and SE. In addition, the fuzzy-based decision is employed to achieve better Pareto optimality. The performance of the proposed HTSA approach is analyzed using different resource allocation parameters and validated through simulation results.
ISSN:1424-8220
1424-8220
DOI:10.3390/s22020451