Towards capturing representative AS-level Internet topologies
SIGMETRICS '02 Proceedings of the 2002 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Network topology generators: degree-based vs. structural
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Handbook of Graphs and Networks: From the Genome to the Internet
Handbook of Graphs and Networks: From the Genome to the Internet
Heuristically Optimized Trade-Offs: A New Paradigm for Power Laws in the Internet
ICALP '02 Proceedings of the 29th International Colloquium on Automata, Languages and Programming
Fast accurate computation of large-scale IP traffic matrices from link loads
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
An information-theoretic approach to traffic matrix estimation
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
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
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The structure of complex networks has been widely described as scale-free networks generated by the preferential attachment model. However, these models do not take into account the more detailed description of the underlying topological physical structure observed in real networks. In this paper, we propose a new simple synthetic model of the Internet's router-level topology based on Heuristically Optimized Tradeoffs (HOT) concept. The trade-offs between system throughput and the technological and economic constraints that are crucial when designing the synthetic system. We propose a new edge rewiring/addition process for a small-world model with tunable parameters to address the aforementioned issues for high variability in backbone core structure connectivity. Our proposal approach can reproduce the low-likelihood topology metric (topological disassortativity of real networks) and can satisfy the small-world effect at the same time to achieve reasonably "good" network functional requirements.