A quantitative comparison of graph-based models for Internet topology
IEEE/ACM Transactions on Networking (TON)
On routes and multicast trees in the Internet
ACM SIGCOMM Computer Communication Review
ISP survival guide: strategies for running a competitive ISP
ISP survival guide: strategies for running a competitive ISP
Buy-at-bulk network design: approximating the single-sink edge installation problem
SODA '97 Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms
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 the economics of Internet peering
Netnomics
Computer
Measuring ISP topologies with rocketfuel
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Network topology generators: degree-based vs. structural
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
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
The Access Network Design Problem
FOCS '98 Proceedings of the 39th Annual Symposium on Foundations of Computer Science
An Approach to Optimal Peering Between Autonomous Systems in the Internet
IC3N '98 Proceedings of the International Conference on Computer Communications and Networks
Designing Networks Incrementally
FOCS '01 Proceedings of the 42nd IEEE symposium on Foundations of Computer Science
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
Does AS size determine degree in as topology?
ACM SIGCOMM Computer Communication Review - Special issue on wireless extensions to the internet
IEEE Communications Magazine
Conductance and congestion in power law graphs
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer 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
Topology generation based on network design heuristics
CoNEXT '05 Proceedings of the 2005 ACM conference on Emerging network experiment and technology
Generating representative ISP topologies from first-principles
Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Modeling internet topology dynamics
ACM SIGCOMM Computer Communication Review
Redesigning network topology with technology considerations
International Journal of Network Management
Environments for multiagent systems state-of-the-art and research challenges
E4MAS'04 Proceedings of the First international conference on Environments for Multi-Agent Systems
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We propose a novel approach to the study of Internet topology in which we use an optimization framework to model the mechanisms driving incremental growth. While previous methods of topology generation have focused on explicit replication of statistical properties, such as node hierarchies and node degree distributions, our approach addresses the economic tradeoffs, such as cost and performance, and the technical constraints faced by a single ISP in its network design. By investigating plausible objectives and constraints in the design of actual networks, observed network properties such as certain hierarchical structures and node degree distributions can be expected to be the natural by-product of an approximately optimal solution chosen by network designers and operators. In short, we advocate here essentially an approach to network topology design, modeling, and generation that is based on the concept of Highly Optimized Tolerance (HOT). In contrast with purely descriptive topology modeling, this opens up new areas of research that focus on the causal forces at work in network design and aim at identifying the economic and technical drivers responsible for the observed large-scale network behavior. As a result, the proposed approach should have significantly more predictive power than currently pursued efforts and should provide a scientific foundation for the investigation of other important problems, such as pricing, peering, or the dynamics of routing protocols.