Joint Allocation of Wireless Resource and Computing Capability in MEC-Enabled Vehicular Network
Joint Allocation of Wireless Resource and Computing Capability in MEC-Enabled Vehicular Network
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DOI：
10.23919/jcc.2021.06.006
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发表时间：
2021-06-01
影响因子：
4.1
通讯作者：
Wu, Xunchao
中科院分区：
文献类型：
--
作者：
Hou, Yanzhao;Wang, Chengrui;Wu, Xunchao
在无线资源和计算资源有限的MEC使能车载网络中，严格的延迟和高可靠性要求是具有挑战性的问题。为了降低网络总时延，同时保证车载UE（VUE）的可靠性，提出了一种无线资源和MEC计算资源联合分配（JAWC）算法。JAWC算法包括两个步骤：V2X链路聚类和MEC计算资源调度。在V2X链路分簇中，提出了基于频谱半径的干扰消除方案（SR-IC）以获得最优资源分配矩阵。通过将SINR的计算转化为矩阵最大行和的计算，可以约束VUE的累积干扰，有效降低SINR的计算复杂度。在MEC计算资源调度中，通过将原优化问题转化为凸优化问题，得到VUE和MEC计算资源分配的最优任务卸载比例。仿真结果进一步表明，JAWC算法能够在保证VUE通信可靠性的同时，显著降低VUE的总时延。
In MEC-enabled vehicular network with limited wireless resource and computation resource, stringent delay and high reliability requirements are challenging issues. In order to reduce the total delay in the network as well as ensure the reliability of Vehicular UE (VUE), a Joint Allocation of Wireless resource and MEC Computing resource (JAWC) algorithm is proposed. The JAWC algorithm includes two steps: V2X links clustering and MEC computation resource scheduling. In the V2X links clustering, a Spectral Radius based Interference Cancellation scheme (SR-IC) is proposed to obtain the optimal resource allocation matrix. By converting the calculation of SINR into the calculation of matrix maximum row sum, the accumulated interference of VUE can be constrained and the the SINR calculation complexity can be effectively reduced. In the MEC computation resource scheduling, by transforming the original optimization problem into a convex problem, the optimal task offloading proportion of VUE and MEC computation resource allocation can be obtained. The simulation further demonstrates that the JAWC algorithm can significantly reduce the total delay as well as ensure the communication reliability of VUE in the MEC-enabled vehicular network.