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arXiv 2004.00159eess.SYcs.SY
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受随机信息物理扰动影响的动态流网络的弹性控制

Resilient Control of Dynamic Flow Networks Subject to Stochastic Cyber-Physical Disruptions

Yu Tang, Li Jin

AI总结:

本文研究随机信息物理扰动下动态流网络的吞吐量弹性,利用 Lyapunov 函数与单调动力学分析稳定性,并针对不同网络条件给出达到割容量界或保证吞吐量的控制策略。

摘要:

交通和通信等现代网络系统容易受到信息物理扰动,从而遭受效率损失。本文从吞吐量角度研究网络弹性,并开发弹性控制以提高吞吐量。我们考虑允许拥塞传播的单商品网络,并应用 Markov 过程对扰动切换进行建模。在吞吐量分析方面,我们首先利用对拥堵回溢的洞察提出新颖的 Lyapunov 函数,随后利用单调网络动力学降低验证稳定性条件的计算成本。在控制设计方面,我们证明:(i)对于具有无限链路存储空间的网络,存在一种开环控制,可达到最小期望割容量;(ii)对于扰动可观测且扰动会限制最大发送和/或接收流的网络,存在一种依赖模态的控制,可达到期望最小割容量;(iii)对于一般网络,存在一种具有吞吐量保证的闭环控制。我们还针对一组数值算例推导了弹性评分的下界,并验证了采用本文方法带来的弹性提升。

英文摘要:

Modern network systems, such as transportation and communication systems, are prone to cyber-physical disruptions and thus suffer efficiency loss. This paper studies network resiliency, in terms of throughput, and develops resilient control to improve throughput. We consider single-commodity networks that admit congestion propagation. We also apply a Markov process to model disruption switches. For throughput analysis, we first use insights into congestion spillback to propose novel Lyapunov functions and then exploit monotone network dynamics to reduce computational costs of verifying stability conditions. For control design, we show that (i) for a network with infinite link storage space, there exists an open-loop control that attains the min-expected-cut capacity; (ii) for a network with observable disruptions that restrict maximum sending and/or receiving flows, there exists a mode-dependent control that attains the expected-min-cut capacity; (iii) for general networks, there exists a closed-loop control with throughput guarantees. We also derive lower bounds of resiliency scores for a set of numerical examples and verify resiliency improvement with our method.

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。

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