Latency Minimization for UAV-Assisted MEC Networks With Blockchain

被引:5
作者
Wang, Chen [1 ,2 ]
Zhai, Daosen [2 ,3 ]
Zhang, Ruonan [1 ]
Li, Huan [4 ]
Richard Yu, Fei [4 ]
机构
[1] Northwestern Polytech Univ, Sch Elect & Informat, Xian 710072, Shaanxi, Peoples R China
[2] Northwestern Polytech Univ, Res & Dev Inst, Shenzhen 518063, Peoples R China
[3] Northwestern Polytech Univ, Sch Elect & Informat, Xian 710072, Peoples R China
[4] Carleton Univ, Dept Syst & Comp Engn, Ottawa, ON K1S 5B6, Canada
基金
中国国家自然科学基金;
关键词
Blockchains; Autonomous aerial vehicles; Servers; Task analysis; Resource management; Data processing; Network architecture; MEC; UAV; blockchain; wireless networks; RESOURCE-ALLOCATION; NOMA; OPTIMIZATION; 5G;
D O I
10.1109/TCOMM.2024.3406400
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Integrating the unmanned aerial vehicles (UAVs) assisted mobile edge computing (MEC) network with the blockchain technology emerges its superiority in the network utilization, differentiated service, and security, which has been regarded as a promising technique for time-critical applications. In this paper, we propose a UAV-assisted MEC network architecture and a comprehensive data processing flow, where the UAVs cooperate with the base station in computation as edge servers and act as blockchain nodes. We formulate an optimization problem that jointly considers UAVs' position, data offloading, and resource allocation for minimizing the total time consumption of data processing. To address this problem, we decouple it as three tractable subproblems and propose a Block Coordinate Descent (BCD)-based iterative algorithm. In addition, we analyze the task migration and resource allocation problem in computation, and obtain analytical solutions by the Karush-Kuhn-Tucker (KKT) conditions. The simulated results indicate that the proposed algorithm leads to substantial performance gains.
引用
收藏
页码:6854 / 6866
页数:13
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