OCCAM: An Optimization-Based Approach to Network Inference
Anirudh Sabnis, Ramesh K. Sitaraman, Donald Towsley

TL;DR
OCCAM is a novel optimization-based method that accurately infers the internal structure and routing paths of communication networks from peripheral measurements, validated on real-world ISP networks.
Contribution
It introduces the first method capable of inferring complete network topology and routing paths using a mixed-integer bilinear optimization framework.
Findings
Achieves 93% network similarity score in topology inference.
Infers routing paths with a path edit distance of 0.20.
Remains effective with 20-30% measurement errors.
Abstract
We study the problem of inferring the structure of a communication network based only on network measurements made from a set of hosts situated at the network periphery. Our novel approach called "OCCAM" is based on the principle of occam's razor and finds the "simplest" network that explains the observed network measurements. OCCAM infers the internal topology of a communication network, including the internal nodes and links of the network that are not amenable to direct measurement. In addition to network topology, OCCAM infers the routing paths that packets take between the hosts. OCCAM uses path metrics measurable from the hosts and expresses the observed measurements as constraints of a mixed-integer bilinear optimization problem that can then be feasibly solved to yield the network topology and the routing paths. We empirically validate OCCAM on a wide variety of real-world ISP…
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Taxonomy
TopicsSoftware-Defined Networks and 5G · Network Security and Intrusion Detection · Network Packet Processing and Optimization
