Paper Info
Title
An Efficient Pareto Optimal Resource Allocation Scheme in Cognitive Radio-Based Internet of Things Networks
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.
Year
DOI
Venue
2022
10.3390/s22020451
SENSORS
Keywords
DocType
Volume
pareto optimality, energy efficiency, spectral efficiency, resource allocation, CR-IoT networks
Journal
22
Issue
ISSN
Citations 
2
1424-8220
1
PageRank 
References 
Authors
0.35
0
7
Name
Order
Citations
PageRank
Shahzad Latif110.35
Suhail Akraam210.35
Tehmina Karamat310.35
Muhammad Attique Khan46911.89
Chadi Altrjman510.35
Senghour Mey610.35
Yunyoung Nam731.87