无线供能移动边缘计算系统的安全卸载优化

针对能量受限的多用户移动边缘计算（MEC）系统存在恶意窃听节点的问题，提出一种联合无线能量传输（WPT）和MEC的安全部分计算卸载方案。该方法以系统接入点（AP）能耗最小化为优化目标，在计算延迟、安全卸载和能量捕获约束条件下，联合优化AP能量传输协方差矩阵、本地CPU频率、用户卸载比特数、用户卸载时间分配以及用户传输功率。针对AP能耗最小化问题为非凸问题，首先采用凸差分算法（DCA）将原始非凸问题转换为凸问题，然后采用拉格朗日对偶法以半封闭形式获得问题最优解。当计算任务数为5×10⁵比特时，与本地计算和安全全部计算卸载方法相比，安全部分卸载方案的能量消耗分别降低了61.3%和84.4%；当窃听节点距离超过25 m时，安全部分卸载方案所消耗的能量远小于本地计算和安全全部计算卸载。仿真实验结果表明，在保证物理层安全卸载的情况下，所提方案能够有效降低AP能耗、提高系统性能增益。

Secure offloading optimization of wireless powered mobile edge computing system

Aiming at the problem of malicious eavesdropping nodes in the energy limited multi-user Mobile Edge Computing （MEC） system， a joint Wireless Power Transfer （WPT） and MEC secure partial computing offloading programme was proposed. In order to minimize the energy consumption of the system Access Point （AP）， the AP energy transmission covariance matrix， local CPU frequency， user unloading bits， user offloading time allocation and user transmission power were jointly optimized under the constraints of computing delay， secure offloading and energy capture. For the AP energy consumption minimization was a non-convex problem， firstly， the original non-convex problem was transformed into a convex problem by Difference of Convex Algorithm （DCA）. Then， the optimal solution of the problem was obtained in semi-closed form by Lagrange duality method. When the number of computing tasks is 5 × 10⁵ bits， compared with local computing offloading and secure full computing offloading， the energy consumption of secure partial offloading scheme was reduced by 61.3% and 84.4%， respectively； when the distance between eavesdropping nodes exceeds 25 m， the energy consumed by the secure partial offloading scheme is much less than those of local computing offloading and secure full computing offloading. The simulation results show that the proposed scheme can effectively reduce AP power consumption and enhance system performance gain while ensuring the secure offloading of the physical layer.