Joint Encryption and Optimization for 6G MEC-Enabled IoT Networks
With the advent of advancements in future sixth-generation (6G) communication systems, Internet of Things (IoT) devices, characterized by their limited computational and communication capacities, have become integral in our lives. These devices are deployed extensively to gather vast amounts of data...
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IEEE
2025-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/10979853/ |
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| author | Manzoor Ahmed Wali Ullah Khan Fatma S. Alrayes Yahia Said Ali M. Al-Sharafi Mi-Hye Kim Khongorzul Dashdondov Inam Ullah |
| author_facet | Manzoor Ahmed Wali Ullah Khan Fatma S. Alrayes Yahia Said Ali M. Al-Sharafi Mi-Hye Kim Khongorzul Dashdondov Inam Ullah |
| author_sort | Manzoor Ahmed |
| collection | DOAJ |
| description | With the advent of advancements in future sixth-generation (6G) communication systems, Internet of Things (IoT) devices, characterized by their limited computational and communication capacities, have become integral in our lives. These devices are deployed extensively to gather vast amounts of data in real-time applications. However, their restricted battery life and computational resources present significant challenges in meeting the requirements of advanced communication systems. Mobile Edge Computing (MEC) has emerged as a promising solution to these challenges within the IoT realm in recent years. Despite its potential, securing MEC infrastructure in the context of IoT remains an open task. This study explores the operational dynamics of a secured IoT-enabled MEC infrastructure, focusing on providing real-time, on-demand, secure computational resources to low-powered IoT devices. It outlines a joint optimization problem to maximize computational throughput, minimize device energy consumption, reduce computational latency, and mitigate security overhead. An optimization algorithm is introduced to address these challenges by jointly allocating resources, thereby optimizing throughput, conserving energy, and meeting latency benchmarks through dynamic system adaptation. The effectiveness of the proposed model and algorithm is demonstrated through comparisons with relevant benchmark schemes, highlighting its efficiency in various scenarios. This work showcases the potential of advancements in encryption to deliver scalable security solutions with reduced resource consumption as the number of devices increases. |
| format | Article |
| id | doaj-art-df7a3006ef994832bb8fc91036f82e7f |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-df7a3006ef994832bb8fc91036f82e7f2025-08-20T02:57:32ZengIEEEIEEE Access2169-35362025-01-0113797577977010.1109/ACCESS.2025.356541510979853Joint Encryption and Optimization for 6G MEC-Enabled IoT NetworksManzoor Ahmed0https://orcid.org/0000-0002-0459-9845Wali Ullah Khan1https://orcid.org/0000-0003-1485-5141Fatma S. Alrayes2https://orcid.org/0000-0002-1644-8526Yahia Said3https://orcid.org/0000-0003-0613-4037Ali M. Al-Sharafi4https://orcid.org/0009-0000-0938-4969Mi-Hye Kim5Khongorzul Dashdondov6Inam Ullah7https://orcid.org/0000-0002-5879-569XSchool of Computer and Information Science, Institute for AI Industrial Technology Research, Hubei Engineering University, Xiaogan, ChinaInterdisciplinary Centre for Security, Reliability, and Trust (SnT), University of Luxembourg, Luxembourg City, LuxembourgDepartment of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box, 84428, Riyadh, Saudi ArabiaCenter for Scientific Research and Entrepreneurship, Northern Border University, Arar, Saudi ArabiaDepartment of Computer Science and Artificial Intelligence, College of Computing and Information Technology, University of Bisha, Bisha, Saudi ArabiaDepartment of Computer Engineering, Chungbuk National University, Cheongju-si, Chungbuk, Republic of KoreaDepartment of Computer Engineering, College of IT Convergence, Gachon University, Seongnam, Republic of KoreaDepartment of Computer Engineering, Gachon University, Seongnam, Republic of KoreaWith the advent of advancements in future sixth-generation (6G) communication systems, Internet of Things (IoT) devices, characterized by their limited computational and communication capacities, have become integral in our lives. These devices are deployed extensively to gather vast amounts of data in real-time applications. However, their restricted battery life and computational resources present significant challenges in meeting the requirements of advanced communication systems. Mobile Edge Computing (MEC) has emerged as a promising solution to these challenges within the IoT realm in recent years. Despite its potential, securing MEC infrastructure in the context of IoT remains an open task. This study explores the operational dynamics of a secured IoT-enabled MEC infrastructure, focusing on providing real-time, on-demand, secure computational resources to low-powered IoT devices. It outlines a joint optimization problem to maximize computational throughput, minimize device energy consumption, reduce computational latency, and mitigate security overhead. An optimization algorithm is introduced to address these challenges by jointly allocating resources, thereby optimizing throughput, conserving energy, and meeting latency benchmarks through dynamic system adaptation. The effectiveness of the proposed model and algorithm is demonstrated through comparisons with relevant benchmark schemes, highlighting its efficiency in various scenarios. This work showcases the potential of advancements in encryption to deliver scalable security solutions with reduced resource consumption as the number of devices increases.https://ieeexplore.ieee.org/document/10979853/6GInternet of Things (IoT)mobile edge computing (MEC)computational throughputenergy consumptioncomputational latency |
| spellingShingle | Manzoor Ahmed Wali Ullah Khan Fatma S. Alrayes Yahia Said Ali M. Al-Sharafi Mi-Hye Kim Khongorzul Dashdondov Inam Ullah Joint Encryption and Optimization for 6G MEC-Enabled IoT Networks IEEE Access 6G Internet of Things (IoT) mobile edge computing (MEC) computational throughput energy consumption computational latency |
| title | Joint Encryption and Optimization for 6G MEC-Enabled IoT Networks |
| title_full | Joint Encryption and Optimization for 6G MEC-Enabled IoT Networks |
| title_fullStr | Joint Encryption and Optimization for 6G MEC-Enabled IoT Networks |
| title_full_unstemmed | Joint Encryption and Optimization for 6G MEC-Enabled IoT Networks |
| title_short | Joint Encryption and Optimization for 6G MEC-Enabled IoT Networks |
| title_sort | joint encryption and optimization for 6g mec enabled iot networks |
| topic | 6G Internet of Things (IoT) mobile edge computing (MEC) computational throughput energy consumption computational latency |
| url | https://ieeexplore.ieee.org/document/10979853/ |
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