论文标题
MMWave网络的主动弹性传输和调度机制
Proactive Resilient Transmission and Scheduling Mechanisms for mmWave Networks
论文作者
论文摘要
本文旨在开发弹性传输机制，以在任意毫米波（MMWAVE）网络中适当地跨多个路径分发流量。主要贡献包括：（a）开发主动传输机制，这些机制提前针对网络中断，同时达到高端数据包率； （b）有效选择（在网络大小的多项式时间中）的启发式路径选择算法的设计多个具有高包装速率的弹性路径； （c）开发一种混合调度算法，该算法将所提出的路径选择算法与基于深入的强化学习（DRL）的在线方法相结合，以分散对阻塞链路和失败路径的分散化适应性。为了实现链接失败的韧性，研究了一种适应通过网络的信息流的最先进的软批评者DRL算法。所提出的调度算法鲁棒可以适应不同的拓扑，通道和阻塞实现的失败，同时提供了较高的性能，而不是替代算法。
This paper aims to develop resilient transmission mechanisms to suitably distribute traffic across multiple paths in an arbitrary millimeter-wave (mmWave) network. The main contributions include: (a) the development of proactive transmission mechanisms that build resilience against network disruptions in advance, while achieving a high end-to-end packet rate; (b) the design of a heuristic path selection algorithm that efficiently selects (in polynomial time in the network size) multiple proactively resilient paths with high packet rates; and (c) the development of a hybrid scheduling algorithm that combines the proposed path selection algorithm with a deep reinforcement learning (DRL) based online approach for decentralized adaptation to blocked links and failed paths. To achieve resilience to link failures, a state-of-the-art Soft Actor-Critic DRL algorithm, which adapts the information flow through the network, is investigated. The proposed scheduling algorithm robustly adapts to link failures over different topologies, channel and blockage realizations while offering a superior performance to alternative algorithms.
