Survivability of time-varying networks

Abstract

Time-varying graphs are a useful model for networks with dynamic connectivity such as mmWave networks and vehicular networks, yet, despite their great modeling power, many important features of time-varying graphs are still poorly understood. In this thesis, 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 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 timevarying 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 in the robust design of a real-world bus communication network.