What question did this study set out to answer?

The central aim is to explore energy-efficient resource allocation while ensuring fairness in MEC-assisted high-speed rail networks.

April 23, 2026Open Access

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Age-of-Computing Constrained Fairness-aware Energy Efficient Resource Allocation in MEC-assisted HSRNs

YLYeshen LiBeijing Jiaotong University KXKe XiongBeijing Jiaotong University ZZZhifei ZhangBeijing Jiaotong University

Key Points

The central aim is to explore energy-efficient resource allocation while ensuring fairness in MEC-assisted high-speed rail networks.
Utilized a computing constrained algorithm for resource allocation.
Focused on energy efficiency and fairness metrics in resource distribution.
Analyzed the performance impact on high-speed rail network operations.
Achieved a significant reduction in energy consumption during resource allocation.
Improved fairness levels among users in resource access.
Enhanced overall efficiency of the MEC-assisted system.

Abstract

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Age-of-Computing Constrained Fairness-aware Energy Efficient Resource Allocation in MEC-assisted HSRNs

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