空地协同隐蔽移动边缘计算系统的能耗优化算法

Energy Consumption Optimization for Air-Ground Cooperation Based Covert Mobile Edge Computing System

针对实际应用中难以获取看守者准确位置信息的问题,提出了鲁棒的空地协同隐蔽移动边缘计算系统的能耗优化算法。在只知道看守者估计位置信息的条件下,分别从看守者和无人机的角度分析隐蔽性约束,通过联合优化计算任务分配因子、无人机-地面基站关联因子、无人机功率以及飞行轨迹,建立了无人机的加权总能耗最小化问题的数学模型。基于块坐标下降法、S-引理和连续凸近似法,提出了一种带参数的三阶段高效交替迭代优化算法,解决所提出的非凸优化问题。仿真实验结果表明,所提算法在节省能耗的同时,增大了给定隐蔽率约束下的卸载任务量,且具有良好的收敛性。

Under the condition that only the estimated location information of Willie is known,the covertness constraints are analyzed from the perspective of the warden node Willie and the unmanned aerial vehicle respectively.Then the optimization problem to minimize the weighted total energy consumption of the unmanned aerial vehicle is established by jointly optimizing the computation task allocation factor,the unmanned aerial vehicle-ground base station association factor,the unmanned aerial vehicle power and the unmanned d aerial vehicletrajectory.To tackle the formulated non-convex optimization problem,an efficient three-stage alternating iterative optimization algorithm with the parameter based on block coordinate descent method,S-procedure and successive convex approximation method is proposed.Simulation results evidently demonstrate that the proposed algorithm can save energy consumption and offload more computing tasks to the ground base stations under given covert rate constraints,and has a desirable convergence.