Optimal Monitor Assignment for Preferential Link Tomography in Communication Networks

Abstract

Inferring fine-grained link metrics by using aggregated path measurements, known as network tomography, is an effective and efficient way to facilitate various network operations, such as network monitoring, load balancing, and failure diagnosis. Given the network topology and a set of interesting links, we study the problem of calculating the link metrics of these links by end-to-end cycle-free path measurements among selected monitors, i.e., preferential link tomography. Since assigning nodes as monitors usually requires non-negligible operational cost, we focus on assigning a minimum number of monitors to identify these interesting links. We propose an optimal monitor assignment (OMA) algorithm for preferential link tomography in communication networks. OMA first partitions the graph representing the network topology into multiple graph components. Then, OMA carefully assigns monitors inside each graph component and at the boundaries of multiple graph components. We theoretically prove the optimality of OMA by proving: 1) the monitors assigned by OMA are able to identify all interesting links and 2) the number of monitors assigned by OMA is minimal. We also implement OMA and evaluate it through extensive simulations based on both real topologies and synthetic topologies. Compared with two baseline approaches, OMA reduces the number of monitors assigned significantly in various network settings.