Sparse Resource Allocation for Control of Spreading Processes via Convex Optimization

Multi-Stage Sparse Resource Allocation for Control of Spreading Processes over Networks

In this paper we propose a method for sparse dynamic allocation of resources to bound the risk of spreading processes, such as epidemics and wildfires, using convex optimization and dynamic programming techniques. Here, risk is defined as the risk of an outbreak, i.e. the product of the probability of an outbreak occurring over a time interval and the future impact of that outbreak, and we can allocate budgeted resources each time step to bound or minimize the risk. Our method in particular provides sparsity of resources, which is important due to the large network structures involved with spr…

Sparse Resource Allocation for Spreading Processes on Temporal-Switching Networks

Spreading processes, e.g. epidemics, wildfires and rumors, are often modeled on static networks. However, their underlying network structures, e.g. changing contacts in social networks, different weather forecasts for wildfires, are due to ever-changing circumstances inherently time-varying in nature. In this paper, we therefore, propose an optimization framework for sparse resource allocation for control of spreading processes over temporal networks with known connectivity patterns. We use convex optimization, in particular exponential cone programming, and dynamic programming techniques to b…

Model Predictive Control of Spreading Processes via Sparse Resource Allocation

In this paper, we propose a model predictive control (MPC) method for real-time intervention of spreading processes, such as epidemics and wildfire, over large-scale networks. The goal is to allocate budgeted resources each time step to minimize the risk of an undetected outbreak, i.e. the product of the probability of an outbreak and the impact of that outbreak. By using dynamic programming relaxation, the MPC controller is reformulated as a convex optimization problem, in particular an exponential cone programming. We also provide sufficient conditions for the closed-loop risks to asymptotic…

网络中对抗传播过程的最优资源分配

Optimal Resource Allocation for Network Protection Against Spreading Processes

研究如何在任意有向网络中通过节点分布保护资源来遏制传播过程，分析预防和纠正资源的最优分配及最小预算问题，采用几何规划在多项式时间内解决。

Minimizing the Risk of Spreading Processes via Surveillance Schedules and Sparse Control

In this paper, we propose an optimization framework that combines surveillance schedules and sparse control to bound the risk of spreading processes such as epidemics and wildfires. Here, risk is considered the risk of an undetected outbreak, i.e. the product of the probability of an outbreak and the impact of that outbreak, and we can bound or minimize the risk by resource allocation and persistent monitoring schedules. The presented framework utilizes the properties of positive systems and convex optimization to provide scalable algorithms for both surveillance and intervention purposes. We …

网络交通控制以防止传播过程

Traffic Control for Network Protection Against Spreading Processes

本文研究了通过优化有限预算分配三种保护资源来遏制病毒传播过程，提出利用几何规划在任意加权有向接触网络中实现多项式时间解决方案。