多跳无线网络中一类通用的吞吐量最优路由策略
A General Class of Throughput Optimal Routing Policies in Multi-hop Wireless Networks
AI总结：
针对多跳约束排队网络中的吞吐量最优路由/调度问题，提出一类基于连续、可微、分段二次李雅普诺夫函数的通用路由策略，并证明其吞吐量最优性，同时恢复背压路由的吞吐量最优性并证明拥塞分集机会路由的吞吐量最优性。
摘要：
本文考虑具有随机连通性的多跳约束排队网络中的吞吐量最优路由/调度问题，其特例包括机会多跳无线网络和输入排队交换结构。设计吞吐量最优路由策略的主要挑战与识别具有负期望漂移的适当且通用的李雅普诺夫函数密切相关。文献中少数已知的吞吐量最优策略是使用队列积压的简单二次或指数李雅普诺夫函数构建的，因此它们寻求独立于网络拓扑地平衡队列积压。通过考虑一类连续、可微且分段二次的李雅普诺夫函数，本文提供了一大类吞吐量最优路由策略。所提出的李雅普诺夫函数类允许路由策略在状态空间的大部分区域沿短路径控制流量，同时确保负期望漂移。这种结构使得能够设计一大类路由策略。特别地，除了恢复众所周知的背压路由策略的吞吐量最优性之外，还证明了具有拥塞分集的机会路由策略是吞吐量最优的。
英文摘要：
This paper considers the problem of throughput optimal routing/scheduling in a multi-hop constrained queueing network with random connectivity whose special case includes opportunistic multi-hop wireless networks and input-queued switch fabrics. The main challenge in the design of throughput optimal routing policies is closely related to identifying appropriate and universal Lyapunov functions with negative expected drift. The few well-known throughput optimal policies in the literature are constructed using simple quadratic or exponential Lyapunov functions of the queue backlogs and as such they seek to balance the queue backlogs across network independent of the topology. By considering a class of continuous, differentiable, and piece-wise quadratic Lyapunov functions, this paper provides a large class of throughput optimal routing policies. The proposed class of Lyapunov functions allow for the routing policy to control the traffic along short paths for a large portion of state-space while ensuring a negative expected drift. This structure enables the design of a large class of routing policies. In particular, and in addition to recovering the throughput optimality of the well known backpressure routing policy, an opportunistic routing policy with congestion diversity is proved to be throughput optimal.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
