Trust-Centric and Economically Optimized Resource Management for 6G-Enabled Internet of Things Environment
The continuous evolvement of IoT networks has introduced significant optimization challenges, particularly in resource management, energy efficiency, and performance enhancement. Most state-of-the-art solutions lack adequate adaptability and runtime cost-efficiency in dynamic 6G-enabled IoT environm...
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| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Computers |
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| Online Access: | https://www.mdpi.com/2073-431X/14/1/10 |
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| author | Osama Z. Aletri Kamran Ahmad Awan Abdullah M. Alqahtani |
| author_facet | Osama Z. Aletri Kamran Ahmad Awan Abdullah M. Alqahtani |
| author_sort | Osama Z. Aletri |
| collection | DOAJ |
| description | The continuous evolvement of IoT networks has introduced significant optimization challenges, particularly in resource management, energy efficiency, and performance enhancement. Most state-of-the-art solutions lack adequate adaptability and runtime cost-efficiency in dynamic 6G-enabled IoT environments. Accordingly, this paper proposes the Trust-centric Economically Optimized 6G-IoT (TEO-IoT) framework, which incorporates an adaptive trust management system based on historical behavior, data integrity, and compliance with security protocols. Additionally, dynamic pricing models, incentive mechanisms, and adaptive routing protocols are integrated into the framework to optimize resource usage in diverse IoT scenarios. TEO-IoT presents an end-to-end solution for security management and network traffic optimization, utilizing advanced algorithms for trust score estimation and anomaly detection. The proposed solution is emulated using the NS-3 network simulator across three datasets: Edge-IIoTset, N-BaIoT, and IoT-23. Results demonstrate that TEO-IoT achieves an optimal resource usage of 92.5% in Edge-IIoTset and reduces power consumption by 15.2% in IoT-23, outperforming state-of-the-art models like IDSOFT and RAT6G. |
| format | Article |
| id | doaj-art-2a97b7825b3d4f2681df5a8eee33d78d |
| institution | Kabale University |
| issn | 2073-431X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computers |
| spelling | doaj-art-2a97b7825b3d4f2681df5a8eee33d78d2025-01-24T13:27:52ZengMDPI AGComputers2073-431X2024-12-011411010.3390/computers14010010Trust-Centric and Economically Optimized Resource Management for 6G-Enabled Internet of Things EnvironmentOsama Z. Aletri0Kamran Ahmad Awan1Abdullah M. Alqahtani2Department of Computing, College of Engineering and Computing, Umm Al-Qura University, Makkah 21955, Saudi ArabiaDepartment of Information Technology, The University of Haripur, Haripur 22620, PakistanDepartment of Electrical and Electronic Engineering, College of Engineering and Computer Science, Jazan University, Jazan 45142, Saudi ArabiaThe continuous evolvement of IoT networks has introduced significant optimization challenges, particularly in resource management, energy efficiency, and performance enhancement. Most state-of-the-art solutions lack adequate adaptability and runtime cost-efficiency in dynamic 6G-enabled IoT environments. Accordingly, this paper proposes the Trust-centric Economically Optimized 6G-IoT (TEO-IoT) framework, which incorporates an adaptive trust management system based on historical behavior, data integrity, and compliance with security protocols. Additionally, dynamic pricing models, incentive mechanisms, and adaptive routing protocols are integrated into the framework to optimize resource usage in diverse IoT scenarios. TEO-IoT presents an end-to-end solution for security management and network traffic optimization, utilizing advanced algorithms for trust score estimation and anomaly detection. The proposed solution is emulated using the NS-3 network simulator across three datasets: Edge-IIoTset, N-BaIoT, and IoT-23. Results demonstrate that TEO-IoT achieves an optimal resource usage of 92.5% in Edge-IIoTset and reduces power consumption by 15.2% in IoT-23, outperforming state-of-the-art models like IDSOFT and RAT6G.https://www.mdpi.com/2073-431X/14/1/10Internet of Thingsresource management6th-generation networktrust managementeconomic optimizationdelay-tolerant routing |
| spellingShingle | Osama Z. Aletri Kamran Ahmad Awan Abdullah M. Alqahtani Trust-Centric and Economically Optimized Resource Management for 6G-Enabled Internet of Things Environment Computers Internet of Things resource management 6th-generation network trust management economic optimization delay-tolerant routing |
| title | Trust-Centric and Economically Optimized Resource Management for 6G-Enabled Internet of Things Environment |
| title_full | Trust-Centric and Economically Optimized Resource Management for 6G-Enabled Internet of Things Environment |
| title_fullStr | Trust-Centric and Economically Optimized Resource Management for 6G-Enabled Internet of Things Environment |
| title_full_unstemmed | Trust-Centric and Economically Optimized Resource Management for 6G-Enabled Internet of Things Environment |
| title_short | Trust-Centric and Economically Optimized Resource Management for 6G-Enabled Internet of Things Environment |
| title_sort | trust centric and economically optimized resource management for 6g enabled internet of things environment |
| topic | Internet of Things resource management 6th-generation network trust management economic optimization delay-tolerant routing |
| url | https://www.mdpi.com/2073-431X/14/1/10 |
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