Latency-aware secure transmission in MEC-assisted HSR communication systems

Hao Xu,Bo Jiang ,Jianfeng Cheng,Ké Li ,Yu Hou

doi:10.1186/s13634-021-00825-4

Hao Xu, Bo Jiang + Show 3 more

Open Access

https://doi.org/10.1186/s13634-021-00825-4

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Abstract

Mobile edge computing can provide short-range cloud computing capability for the mobile users, which is considered to be a promising technology in 5G communication. The mobile users offload some computing tasks to the edge server through the wireless backhaul link, which can reduce the energy consumption and the time latency. Meanwhile, due to the open characteristics of the wireless channel, the offloading tasks through the backhaul link may face the risk of eavesdropping. Therefore, the secure transmission based on physical layer security for the offloading tasks to the edge server is considered. The optimization problem of minimizing the energy consumption for the vehicular stations (VSs) in mobile edge computing-assisted high-speed railway communication system is studied in this paper. The energy consumption of the mobile users is generated by executing the local computing task and by transmitting the partial offloading task to the edge server. In this paper, a novel joint iterative optimization algorithm is proposed. By jointly optimizing the task scheduling, the task offloading and the transmission power, the energy consumption of all VSs is minimized under the constraint of the time latency. Numerical simulation results verify the effectiveness of the proposed algorithm.

Highlights

1.1 Challenges and contributions With the development of 5G wireless communication and the Internet of things (IoTs), new technologies such as virtual reality (VR), augmented reality (AR) and unmanned driving appear [1,2,3]
We mainly study the task offloading problem of minimizing the energy consumption of the vehicular stations (VSs) in mobile edge computing (MEC)-assisted high-speed railway (HSR) wireless communication system
For MEC-assisted HSR wireless communication system, we propose an iterative algorithm to minimize the energy consumption of multiple VSs, while ensuring the latency constraints and the power constraints of the computing tasks

Summary

Introduction

1.1 Challenges and contributions With the development of 5G wireless communication and the Internet of things (IoTs), new technologies such as virtual reality (VR), augmented reality (AR) and unmanned driving appear [1,2,3]. Under the constraints of task execution time, transmission power, computing capacity and front-end transmission data rate, the formulated energy consumption minimization problem was a nonconvex optimization one. Multiple mobile users multi-cell multiple-in multiple-out (MIMO) system with a cloud server was considered in [31]; the energy consumption minimization problem with the latency constraint by jointly optimizing the transmitting precoding matrices and the CPU cycles was studied. The computing offloading strategy of multiple VSs and multiple edge server in MEC-assisted HSR communication system is considered; under the constraints of the safe computing task offloading, transmission latency and transmission power, a novel iterative algorithm to minimize the total energy consumption of multiple VSs is proposed

Methods

Iteration‐based algorithm for MEC‐assisted HSR communication systems

Simulation configuration

Findings

Conclusion