配电网中任务卸载决策与边缘资源分配优化方法

移动边缘计算可以减轻配电网核心网络中海量数据的传输及处理压力,相对于云计算,边缘节点有限的计算能力使边缘资源的高效利用成为挑战。基于此,提出一种配电网中任务卸载决策与边缘资源分配优化方法。在包含多边缘节点多用户设备的配电网场景中,考虑任务随机、资源有限、计算能力不均衡及时延要求高等因素,构建云-边-端三层任务卸载及边缘资源分配优化模型;将优化过程分为计算卸载和资源拍卖两个阶段,在计算卸载阶段设计基于DRL的在线决策算法,在资源拍卖阶段设计基于补偿策略的多轮迭代拍卖算法;提出基于改进DQN算法的任务卸载与资源分配优化方法。仿真结果表明,在动态变化的配电网场景中,所提算法可有效提高系统计算能效和边缘节点效益。

Employment Difficulties and Countermeasures for Art Students in Colleges and Universities

Employment is the principal source of income.The employment of graduates is associated with the satisfaction and sense of gain experienced by thousands of families.In recent years,the number of art students in colleges and universities has grown steadily.However,influenced by various factors,the employment situation of art graduates has become increasingly severe.In this paper,the employment situation and difficulties faced by art graduates are analyzed,and countermeasures for high-quality and full employment are put forward in view of the situation and employment problem faced by art graduates.