Network routing in a dynamic environment

TL;DR

This paper introduces a decision-theoretic framework for network routing in hostile, dynamic environments, emphasizing statistical inference and data fusion to improve route selection amid adversarial threats.

Contribution

It presents a novel approach combining decision theory and statistical analysis for routing in hostile environments, integrating diverse data sources and behavioral modeling.

Findings

Framework effectively incorporates diverse data sources.

Statistical inference enhances route decision-making.

Demonstrates interdisciplinary application of data analysis.

Abstract

Recently, there has been an explosion of work on network routing in hostile environments. Hostile environments tend to be dynamic, and the motivation for this work stems from the scenario of IED placements by insurgents in a logistical network. For discussion, we consider here a sub-network abstracted from a real network, and propose a framework for route selection. What distinguishes our work from related work is its decision theoretic foundation, and statistical considerations pertaining to probability assessments. The latter entails the fusion of data from diverse sources, modeling the socio-psychological behavior of adversaries, and likelihood functions that are induced by simulation. This paper demonstrates the role of statistical inference and data analysis on problems that have traditionally belonged in the domain of computer science, communications, transportation science, and operations research.