Graph-Theoretic Models of Resource Distribution for Cyber-Physical Systems of Disaster-Affected Regions

TL;DR

This paper introduces RADAR, a graph-theoretic framework leveraging SMT algorithms to optimize resource distribution in disaster-affected regions, aiding decision-making during response and preparedness phases.

Contribution

It presents a novel algebraic and graph-based tool-supported framework for modeling and reasoning about resource distribution in cyber-physical disaster management systems.

Findings

Effective routing strategies demonstrated in case study

Framework supports decision-making during disaster response

Applicable to various disaster scenarios

Abstract

We propose a tool-supported framework to reason about requirements constraining resource distributions and devise strategies for routing essential services in a disaster-affected region. At the core of our approach is the Route Advisor for Disaster-Affected Regions (RADAR) framework that operates on high-level algebraic representations of the region, modelled as a cyber-physical system (cps) where resource distribution is carried out over an infrastructure connecting physical geographical locations. The Satisfiable-Modulo Theories (SMT) and graph-theoretic algorithms used by the framework supports disaster management decision-making during response and preparedness phases. We demonstrate our approach on a case study in disaster management and describe scenarios to illustrate the usefulness of RADAR.