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Volume 22
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10.3390/s22020451
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Article

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

by
Shahzad Latif
1,
Suhail Akraam
2,
Tehmina Karamat
3,
Muhammad Attique Khan
4,
Chadi Altrjman
5,
Senghour Mey
6 and
Yunyoung Nam
7,*
1
Shaheed Zulfikar Ali Bhutto Institute of Science and Technology (SZABIST), Islamabad 75600, Pakistan
2
BARANI Institute of Sciences Burewala, JV of PMAS ARID Agriculture University Rawalpindi, Rawalpindi 46000, Pakistan
3
Department of Software Engineering, Foundation University Islamabad, Rawalpindi 46000, Pakistan
4
Department of Computer Science, HITEC University Taxila, Taxila 47080, Pakistan
5
Artificial Intelligence Engineering Department, AI and Robotics Institute, Near East University, Mersin 99138, Turkey
6
Department of ICT Convergence, Soonchunhyang University, Asan 31538, Korea
7
Department of Computer Science and Engineering, Soonchunhyang University, Asan 31538, Korea
*
Author to whom correspondence should be addressed.
Sensors 2022, 22(2), 451; https://doi.org/10.3390/s22020451
Submission received: 1 December 2021 / Revised: 24 December 2021 / Accepted: 4 January 2022 / Published: 7 January 2022
(This article belongs to the Special Issue Sustainable Computing Based on Internet of Things Empowered with Artificial Intelligence and Blockchain)
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Abstract

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.
Keywords: pareto optimality; energy efficiency; spectral efficiency; resource allocation; CR-IoT networks pareto optimality; energy efficiency; spectral efficiency; resource allocation; CR-IoT networks

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MDPI and ACS Style

Latif, S.; Akraam, S.; Karamat, T.; Khan, M.A.; Altrjman, C.; Mey, S.; Nam, Y. An Efficient Pareto Optimal Resource Allocation Scheme in Cognitive Radio-Based Internet of Things Networks. Sensors 2022, 22, 451. https://doi.org/10.3390/s22020451

AMA Style

Latif S, Akraam S, Karamat T, Khan MA, Altrjman C, Mey S, Nam Y. An Efficient Pareto Optimal Resource Allocation Scheme in Cognitive Radio-Based Internet of Things Networks. Sensors. 2022; 22(2):451. https://doi.org/10.3390/s22020451

Chicago/Turabian Style

Latif, Shahzad, Suhail Akraam, Tehmina Karamat, Muhammad Attique Khan, Chadi Altrjman, Senghour Mey, and Yunyoung Nam. 2022. "An Efficient Pareto Optimal Resource Allocation Scheme in Cognitive Radio-Based Internet of Things Networks" Sensors 22, no. 2: 451. https://doi.org/10.3390/s22020451

APA Style

Latif, S., Akraam, S., Karamat, T., Khan, M. A., Altrjman, C., Mey, S., & Nam, Y. (2022). An Efficient Pareto Optimal Resource Allocation Scheme in Cognitive Radio-Based Internet of Things Networks. Sensors, 22(2), 451. https://doi.org/10.3390/s22020451

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