基于车辆边缘计算的用户能耗最小化资源分配研究

User Energy Minimization Resource Allocation in Vehicular Edge Computing

  • 摘要: 考虑车辆时变信道对资源分配策略的影响,构建在保证任务QoS要求下的车载用户终端能量消耗最小化问题。利用车辆信道可预测特性以及李雅普诺夫随机优化理论将原问题分解为计算资源分配和无线资源分配两个子问题。由于计算资源分配子问题是单变量优化问题,因此可以直接得到解决方案。而对于无线资源分配子问题,通过将其转换为单变量优化问题进行求解。基于两个子问题的结果,提出一种联合无线与计算资源分配算法。仿真结果显示,当数据包平均到达速率从20个/时隙增加到40个/时隙时,该算法能耗相较于传统的贪婪算法能耗降低了48.85%。

     

    Abstract: Considering the effect of time-varying channel on the resource allocation scheme, a vehicle user power minimization problem with task QoS requirement constraints is formulated. By utilizing the vehicle channel predictability and Lyapunov theory, the original problem is reformulated as two sub-problems of a single variable, which can be solved easily. Thus an algorithm is proposed to solve these two sub-problems of resource allocation and then a joint radio and computation resource allocation scheme is formed according to the two sub-problems solutions. The simulation results show that the power consumption of the proposed algorithm is decreased by 48.85% compared with traditional greedy algorithm when the data average arrival rate grows from 20 packets/slot to 40 packets/slot.

     

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