PSDEEN: Predictive and Secured Decentralized Energy-Efficient 6G Edge Networks for Industrial Consumer Applications

In smart cities, the Internet of Things (IoT) has increased the development and expansion of communication processes for Industry 5.0. With the integration of edge computing, 6G networks offer dynamic and low-cost services for consumer-centric applications to improve problem-solving abilities. However, heterogeneous services face issues controlling massive traffic on restricted systems and transmission delays. Moreover, due to the limitations of advanced technologies for various constraints, embedded applications experience data management issues and consume additional energy for associated services. In this research, we proposed a predictive distributed energy-efficient edge protocol for consumer industrial systems with the support of trusted communication over the 6G networks. It improved the computation outcomes using intelligent and lightweight power resources for integrated devices. Furthermore, it offers traffic-aware and reliable green energy systems for mobile services, particularly in rural areas. By leveraging the 6G technology for high bandwidth and low latency, edge computing provides consumer data processing closer to IoT devices, enabling on-time, real-time decision-making. It includes load-balancing functionality and increases the sustainability level for industrial applications. Using simulations, significant improvement has been revealed to highlight the potential of the proposed protocol and support the demands of Industry 5.0 for round-trip time by 33%, energy consumption by 39%, end-to-end delay by 41%, and complexity detection 30% than existing work.

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Publication Details

Journal
IEEE Transactions on Consumer Electronics
Published
2025-09-17
DOI
https://doi.org/10.1109/tce.2025.3611275
Primary Topic
Advanced MIMO Systems Optimization
Type
article
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article

PSDEEN: Predictive and Secured Decentralized Energy-Efficient 6G Edge Networks for Industrial Consumer Applications

Ayesha Shafique, Sushil Kumar Singh, Khalid Haseeb, Amjad Rehman et al.
IEEE Transactions on Consumer Electronics
Advanced MIMO Systems Optimization
article

PSDEEN: Predictive and Secured Decentralized Energy-Efficient 6G Edge Networks for Industrial Consumer Applications

Ayesha Shafique, Sushil Kumar Singh, Khalid Haseeb, Amjad Rehman, Abeer Mirdad, Weiwei Jiang
article en

Abstract

In smart cities, the Internet of Things (IoT) has increased the development and expansion of communication processes for Industry 5.0. With the integration of edge computing, 6G networks offer dynamic and low-cost services for consumer-centric applications to improve problem-solving abilities. However, heterogeneous services face issues controlling massive traffic on restricted systems and transmission delays. Moreover, due to the limitations of advanced technologies for various constraints, embedded applications experience data management issues and consume additional energy for associated services. In this research, we proposed a predictive distributed energy-efficient edge protocol for consumer industrial systems with the support of trusted communication over the 6G networks. It improved the computation outcomes using intelligent and lightweight power resources for integrated devices. Furthermore, it offers traffic-aware and reliable green energy systems for mobile services, particularly in rural areas. By leveraging the 6G technology for high bandwidth and low latency, edge computing provides consumer data processing closer to IoT devices, enabling on-time, real-time decision-making. It includes load-balancing functionality and increases the sustainability level for industrial applications. Using simulations, significant improvement has been revealed to highlight the potential of the proposed protocol and support the demands of Industry 5.0 for round-trip time by 33%, energy consumption by 39%, end-to-end delay by 41%, and complexity detection 30% than existing work.

IEEE Transactions on Consumer ElectronicsVol. 71(4)
Beijing University of Posts and Telecommunications (CN), Prince Sultan University (SA), Islamia College University (PK), Marwadi University (IN), Wuxi Taihu Hospital (CN)
Openalex Percentile: Top 76%
Advanced MIMO Systems Optimization
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