The Hazard Value: A Quantitative Network Connectivity Measure Accounting for Failures

To meet their stringent requirements in terms of performance and dependability, communication networks should be "well connected". While classic connectivity measures typically revolve around topological properties, e.g., related to cuts, these measures may not reflect well the degree to which a network is actually dependable. We introduce a more refined measure for network connectivity, the hazard value, which is developed to meet the needs of a real network operator. It accounts for crucial aspects affecting the dependability experienced in practice, including actual traffic patterns, distribution of failure probabilities, routing constraints, and alternatives for services with preferences therein. We analytically show that the hazard value fulfills several fundamental desirable properties that make it suitable for comparing different network topologies with one another, and for reasoning about how to efficiently enhance the robustness of a given network. We also present an optimised algorithm to compute the hazard value and an experimental evaluation against networks from the Internet Topology Zoo and classical datacenter topologies, such as fat trees and BCubes. This evaluation shows that the algorithm computes the hazard value within minutes for realistic networks, making it practically usable for network designers.