6G; computational latency; computational throughput; energy consumption; Internet of Things (IoT); mobile edge computing (MEC); secure encryption; 6g; Communications systems; Computational latency; Computational resources; Computational throughput; Edge computing; Energy-consumption; Internet of thing; Mobile edge computing; Secure encryption; Computer Science (all); Materials Science (all); Engineering (all); Internet of Things; Security; Resource management; Optimization; 6G mobile communication; Encryption; Dynamic scheduling; Computational efficiency; Servers
Abstract :
[en] 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.
Disciplines :
Electrical & electronics engineering
Author, co-author :
Ahmed, Manzoor ; Hubei Engineering University, School of Computer and Information Science, Institute for AI Industrial Technology Research, Xiaogan, China
KHAN, Wali Ullah ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
Alrayes, Fatma S. ; Princess Nourah bint Abdulrahman University, College of Computer and Information Sciences, Department of Information Systems, Riyadh, Saudi Arabia
Said, Yahia ; Northern Border University, Center for Scientific Research and Entrepreneurship, Arar, Saudi Arabia
Al-Sharafi, Ali M. ; University of Bisha, College of Computing and Information Technology, Department of Computer Science and Artificial Intelligence, Bisha, Saudi Arabia
Kim, Mi-Hye; Chungbuk National University, Department of Computer Engineering, Cheongju-si, South Korea
Dashdondov, Khongorzul; Gachon University, College of IT Convergence, Department of Computer Engineering, Seongnam, South Korea
Ullah, Inam ; Gachon University, Department of Computer Engineering, Seongnam, South Korea
External co-authors :
yes
Language :
English
Title :
Joint Encryption and Optimization for 6G MEC-Enabled IoT Networks
Publication date :
2025
Journal title :
IEEE Access
ISSN :
2169-3536
Publisher :
Institute of Electrical and Electronics Engineers Inc.
Princess Nourah bint Abdulrahman University Researchers Supporting Project, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia Northern Border University, Saudi Arabia Deanship of Graduate Studies and Scientific Research at the University of Bisha through the Fast-Track Research Support Program “Regional Innovation Cluster Development (Research and Development) Project (Open Innovation of Base Institutions)” supported by the Ministry of Trade, Industry and Energy
Funding text :
This work was supported in part by the Princess Nourah bint Abdulrahman University Researchers Supporting Project, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia, under Grant PNURSP2025R319; in part by the Northern Border University, Saudi Arabia, under Project NBU-CRP-2025-3030; in part by the Deanship of Graduate Studies and Scientific Research at the University of Bisha through the Fast-Track Research Support Program; and in part by the \u2018\u2018Regional Innovation Cluster Development (Research and Development) Project (Open Innovation of Base Institutions)\u2019\u2019 supported by the Ministry of Trade, Industry and Energy.
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