移动边缘计算中基于改进拍卖模型的计算卸载策略

随着移动互联网业务的快速发展，增强现实、虚拟现实、超清视频等手机应用逐渐普及、IoT应用不断涌现，计算能力和续航能力的不足成为限制智能终端设备成功支撑这些应用的主要瓶颈。针对这一现状，采用计算卸载的方式解决该问题，在多用户多移动边缘服务器的场景下，综合考虑智能设备性能和服务器资源提出了一种基于改进拍卖算法的计算卸载策略。该策略主要包括两个阶段，在卸载决策阶段，通过综合考虑计算任务自身大小、计算需求和服务器计算能力、网络带宽等因素提出了卸载决策的依据；在任务调度阶段，通过综合考虑计算任务的时间需求和MEC服务器计算性能提出了基于改进拍卖算法的任务调度模型。实验证明，提出的计算卸载策略能够有效地降低服务时延，减少智能设备能耗，改善用户体验。

Computational offloading strategy based on improved auction model in mobile edge computing

With the rapid development of mobile Internet services, mobile applications such as augmented reality, virtual reality and ultra clear video have become popular and IoT applications are emerging. The limited computing power and the lack of endurance of smart terminal devices are becoming more and more inadequate for these applications. Aiming at this situation, this paper proposed a computational offloading strategy based on improved auction algorithm under the premise of combining intelligent device performance and server resources in the scenario of multi-user and multi-MEC server. This strategy consisted of two important phases: the offloading decision-making phase and the task scheduling phase. In the first phase, by considering the calculation task size, computing requirements and server computing power, network bandwidth and other factors, it proposed the basis for the uninstallation decision. In second phase, by considering the time requirements of the computing task and the computing performance of the MEC server, it proposed a task scheduling model based on improved auction algorithm. The experiment proves that the proposed computational offloading strategy can effectively reduce the service delay, the energy consumption of smart devices, and improve user satisfaction.