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1.南京邮电大学通信与信息工程学院,江苏 南京 210003
2.南京邮电大学江苏省无线通信重点实验室,江苏 南京 210003
Received:01 March 2025,
Revised:2025-04-24,
Accepted:29 April 2025,
Online First:24 September 2026,
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Yu Xueyong,Yan Yunlong,Tan Zhiwei,et al.Secure edge network offloading strategy based on blockchain and UAVs[J].Chinese Journal on Internet of Things,
余雪勇,晏云龙,谭志伟等.基于区块链和无人机的安全边缘网络卸载策略[J].物联网学报, DOI:10.11959/j.issn.2096-3750.WLW25042.
Yu Xueyong,Yan Yunlong,Tan Zhiwei,et al.Secure edge network offloading strategy based on blockchain and UAVs[J].Chinese Journal on Internet of Things, DOI:10.11959/j.issn.2096-3750.WLW25042.
针对边缘计算中终端接入密集、任务计算压力大的问题,提出了一种基于区块链与无人机(unmanned aerial vehicles,UAVs)的安全边缘计算卸载架构。该架构利用区块链技术整合多个移动边缘计算(mobile edge computing,MEC)集群,实现计算资源的可信协同,同时提升无人机与终端之间信息交互的安全性。首先,为提高效率,该架构对所采用的实用拜占庭容错共识算法进行了优化,旨在减少区块链任务的计算能耗和时延。其次,综合考虑了终端的卸载策略、无人机轨迹以及无人机在完成终端卸载任务和区块链任务中的计算资源分配,构建了一个联合优化问题,目标是最小化整个网络的时延和能耗。最后,由于该问题属于混合整数非线性规划问题,通过交替使用块坐标下降(block coordinate descent,BCD)和连续凸近似(successive convex approximation,SCA)算法来求解。仿真结果表明,所提方案能在保证通信安全的同时,显著地降低系统的时延和能耗,性能优于其他基线算法。
To address the challenges of dense terminal access and high computational pressure in edge computing
a secure edge computing offloading architecture based on blockchain and unmanned aerial vehicles (UAVs) was proposed. The architecture leveraged blockchain technology to integrate multiple mobile edge computing (MEC) clusters
enabling trustworthy collaboration of computing resources while enhancing the security of information exchange between UAVs and terminal devices. Firstly
to improve efficiency
this architecture optimized the adopted practical Byzantine fault tolerance consensus algorithm
aiming to reduce the computational energy consumption and latency of blockchain tasks. Then
considering the terminal offloading strategy
UAV trajectories
and the allocation of computing resources for UAVs in both terminal offloading tasks and blockchain tasks
a joint optimization problem was formulated with the goal of minimizing the overall network latency and energy consumption. Finally
since this problem was a mixed-integer nonlinear programming problem
it was solved by alternately using block coordinate descent (BCD) and successive convex approximation (SCA) algorithms. Simulation results show that the proposed scheme significantly reduces the system latency and the energy consumption while ensuring communication security and outperforms the other baseline algorithms.
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