论文标题
移动边缘计算网络控制：延迟和成本之间的权衡
Mobile Edge Computing Network Control: Tradeoff Between Delay and Cost
论文作者
论文摘要
随着移动边缘计算（MEC）发现广泛使用，以减轻最终用户设备上计算和互动密集型应用程序的计算负担，因此了解最终的延迟和成本性能引起了极大的关注。尽管大多数现有的作品都集中在单跳MEC网络中的单程卸载，但下一代应用程序（例如工业自动化，增强/虚拟现实）需要先进的模型和算法，以动态配置多任务服务，而不是多任务MEC网络。在这项工作中，我们利用动态云网络控制的最新进展提供了对多跳MEC网络的性能的全面研究，解决了多任务卸载，及时的数据包计划以及联合计算和通信资源分配的关键问题。我们基于Lyapunov控制理论提出了一种完全分布的算法，该算法以延迟和成本保证来实现吞吐量 - 最佳性能。仿真结果验证了我们的理论分析，并提供了有关MEC网络中通信和计算资源之间相互作用的有见地的指南。
As mobile edge computing (MEC) finds widespread use for relieving the computational burden of compute- and interaction-intensive applications on end user devices, understanding the resulting delay and cost performance is drawing significant attention. While most existing works focus on singletask offloading in single-hop MEC networks, next generation applications (e.g., industrial automation, augmented/virtual reality) require advance models and algorithms for dynamic configuration of multi-task services over multi-hop MEC networks. In this work, we leverage recent advances in dynamic cloud network control to provide a comprehensive study of the performance of multi-hop MEC networks, addressing the key problems of multi-task offloading, timely packet scheduling, and joint computation and communication resource allocation. We present a fully distributed algorithm based on Lyapunov control theory that achieves throughput-optimal performance with delay and cost guarantees. Simulation results validate our theoretical analysis and provide insightful guidelines on the interplay between communication and computation resources in MEC networks.
