Survivability in Time-varying Networks

TL;DR

This paper introduces a new survivability framework for time-varying networks, proposing metrics analogous to MaxFlow and MinCut, analyzing their properties, and demonstrating their application through simulations on a real-world bus network.

Contribution

It proposes a novel survivability framework and metrics for time-varying networks, addressing limitations of traditional definitions and analyzing their computational complexity.

Findings

Traditional survivability definitions are ineffective for time-varying networks.

New metrics similar to MaxFlow and MinCut are proposed for these networks.

Approximation algorithms are developed for computing the metrics.

Abstract

Time-varying graphs are a useful model for networks with dynamic connectivity such as vehicular networks, yet, despite their great modeling power, many important features of time-varying graphs are still poorly understood. In this paper, we study the survivability properties of time-varying networks against unpredictable interruptions. We first show that the traditional definition of survivability is not effective in time-varying networks, and propose a new survivability framework. To evaluate the survivability of time-varying networks under the new framework, we propose two metrics that are analogous to MaxFlow and MinCut in static networks. We show that some fundamental survivability-related results such as Menger's Theorem only conditionally hold in time-varying networks. Then we analyze the complexity of computing the proposed metrics and develop several approximation algorithms. Finally, we conduct trace-driven simulations to demonstrate the application of our survivability framework to the robust design of a real-world bus communication network.