面向海洋节能边缘计算的任务卸载研究

针对海洋通信网络能源不稳定、时延较长的问题，提出一种混合能量供应的边缘计算卸载方案。对于能量供应问题，移动边缘计算(MEC)服务器集成混合电源和混合接入点，混合电源利用可再生能源为MEC服务器供应能量，采用电力电网作为其补充能源，保证边缘计算系统的可靠运行，船舶用户通过混合接入点广播的射频(RF)信号收集能量。针对任务卸载优化问题，以能耗-时延权衡优化为目标，联合能量收集方法制定任务卸载比例、本地计算能力和发射功率的优化方案，最后利用降维优化算法，将目标函数简化为关于任务卸载比例的一维多约束问题，并利用改进的鲸鱼优化算法获得最优的执行总代价。利用边缘云模拟器EdgeCloudSim仿真的结果表明，所提方案较具有能量收集的资源分配方案和基本海上通信网络优化的方案执行成本分别降低了13.4%和9.6%。

Research on task unloading formarine energy-saving edge computing

Aiming at the problems of unstable energy and long time delay in marine communication network, a hybrid energy supply edge computing offload scheme is proposed. For energy supply, mobile edge computing (MEC) server integrates hybrid power supply and hybrid access point. Hybrid power supply uses renewable energy to supply energy for MEC server, and power grid is used to supplement energy to ensure the reliable operation of the system. Vessel users collect energy through radio frequency (RF) signal broadcast by hybrid access point. Aiming at the optimization problem of task offloading and taking energy delay trade-off optimization as the objective, the optimization scheme of task offloading ratio, local computing power and transmit power is formulated with the energy collection method. Finally, the dimension reduction optimization algorithm is adopted to simplify the objective function to a one-dimensional multi-constraint problem about task offloading ratio, and the whale optimization algorithm is improved to obtain the optimal total execution cost. The simulation results of EdgeCloudSim show that the proposed scheme reduces the execution cost by 13.4% and 9.6% compared with the scheme supporting energy collection and the basic offshore communication network optimization scheme.