On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
A random graph model for massive graphs
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
On inferring autonomous system relationships in the internet
IEEE/ACM Transactions on Networking (TON)
BRITE: An Approach to Universal Topology Generation
MASCOTS '01 Proceedings of the Ninth International Symposium in Modeling, Analysis and Simulation of Computer and Telecommunication Systems
A first-principles approach to understanding the internet's router-level topology
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
Evolution and Structure of the Internet: A Statistical Physics Approach
Evolution and Structure of the Internet: A Statistical Physics Approach
The internet AS-level topology: three data sources and one definitive metric
ACM SIGCOMM Computer Communication Review
Exploring networks with traceroute-like probes: theory and simulations
Theoretical Computer Science - Complex networks
Systematic topology analysis and generation using degree correlations
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
AS relationships: inference and validation
ACM SIGCOMM Computer Communication Review
An Introduction to Copulas (Springer Series in Statistics)
An Introduction to Copulas (Springer Series in Statistics)
On compact routing for the internet
ACM SIGCOMM Computer Communication Review
Functional annotation of regulatory pathways
Bioinformatics
INFOCOM'96 Proceedings of the Fifteenth annual joint conference of the IEEE computer and communications societies conference on The conference on computer communications - Volume 2
Inferring AS relationships: dead end or lively beginning?
WEA'05 Proceedings of the 4th international conference on Experimental and Efficient Algorithms
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
On the scalability of BGP: the role of topology growth
IEEE Journal on Selected Areas in Communications - Special issue title on scaling the internet routing system: an interim report
Toward topology dualism: improving the accuracy of AS annotations for routers
PAM'10 Proceedings of the 11th international conference on Passive and active measurement
SIMROT: a scalable inter-domain routing toolbox
ACM SIGMETRICS Performance Evaluation Review - Special Issue on IFIP PERFORMANCE 2011- 29th International Symposium on Computer Performance, Modeling, Measurement and Evaluation
Sharing graphs using differentially private graph models
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Obtaining provably legitimate internet topologies
IEEE/ACM Transactions on Networking (TON)
On inter-domain name resolution for information-centric networks
IFIP'12 Proceedings of the 11th international IFIP TC 6 conference on Networking - Volume Part I
Building a reliable and high-performance content-based publish/subscribe system
Journal of Parallel and Distributed Computing
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The coarsest approximation of the structure of a complex network, such as the Internet, is a simple undirected unweighted graph. This approximation, however, loses too much detail. In reality, objects represented by vertices and edges in such a graph possess some nontrivial internal structure that varies across and differentiates among distinct types of links or nodes. In this work, we abstract such additional information as network annotations. We introduce a network topology modeling framework that treats annotations as an extended correlation profile of a network. Assuming we have this profile measured for a given network, we present an algorithm to rescale it in order to construct networks of varying size that still reproduce the original measured annotation profile. Using this methodology, we accurately capture the network properties essential for realistic simulations of network applications and protocols, or any other simulations involving complex network topologies, including modeling and simulation of network evolution. We apply our approach to the Autonomous System (AS) topology of the Internet annotated with business relationships between ASs. This topology captures the large-scale structure of the Internet. In depth understanding of this structure and tools to model it are cornerstones of research on future Internet architectures and designs. We find that our techniques are able to accurately capture the structure of annotation correlations within this topology, thus reproducing a number of its important properties in synthetically-generated random graphs.