In this study we mine one of the few sources of public data available about the interdomain peering ecosytem: PeeringDB [1], an online database where participating networks contribute information about their peering policies, traffic volumes and presence at various geographic locations. Although established to support the practical needs of operators, this data also provides a valuable source of information to researchers. Using BGP data to cross-validate three years of PeeringDB snapshots, we find that PeeringDB membership is reasonably representative of the Internet's transit, content, and access providers in terms of business types and geography of participants, and PeeringDB data is generally up-to-date. We find strong correlations among different measures of network size -BGP-advertised address space, PeeringDB-reported traffic volume and presence at peering facilities, and between these size measures and advertised peering policies.
We propose an agent-based network formation model for the Internet at the Autonomous System (AS) level. The proposed model, called GENESIS, is based on realistic provider and peering strategies, with ASes acting in a myopic and decentralized manner to optimize a cost-related fitness function. GENESIS captures key factors that affect the network formation dynamics: highly skewed traffic matrix, policy-based routing, geographic co-location constraints, and the costs of transit/peering agreements. As opposed to analytical game-theoretic models, which focus on proving the existence of equilibria, GENESIS is a computational model that simulates the network formation process and allows us to actually compute distinct equilibria (i.e., networks) and to also examine the behavior of sample paths that do not converge. We find that such oscillatory sample paths occur in about 10% of the runs, and they always involve tier-1 ASes, resembling the tier-1 peering disputes often seen in practice. GENESIS results in many distinct equilibria that are highly sensitive to initial conditions and the order in which ASes (agents) act. This implies that we cannot predict the properties of an individual AS in the Internet. However, certain properties of the global network or of certain classes of ASes are predictable. We also examine whether the underlying game is zero-sum, and identify three sufficient conditions for that property. Finally, we apply GENESIS in a specific "what-if" question, asking how the openness towards peering affects the resulting network in terms of topology, traffic flow and economics. Interestingly, we find that the peering openness that maximizes the fitness of different network classes (tier-1, tier-2 and tier-3 providers) closely matches that seen in real-world peering policies.
Abstract-Peering agreements between Autonomous Systems affect not only the flow of interdomain traffic but also the economics of the entire Internet ecosystem. The conventional wisdom is that transit providers are selective in choosing their settlementfree peers because they prefer to offer revenue-generating transit service to others. Surprisingly, however, a large percentage of transit providers use an Open peering strategy. What causes this large-scale adoption of Open peering, especially among transit providers? More importantly, what is the impact of this peering trend on the economic performance of the population of transit providers? We approach these questions through game-theoretic modeling and agent-based simulations, capturing the dynamics of peering strategy adoption, inter-network formation and interdomain traffic flow. We explain why transit providers gravitate towards Open peering even though that move may be detrimental to their economic fitness. Finally, we examine the impact of an Open peering variant that requires some coordination among providers.
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