Abstract:
The Internet consists of thousands of interconnected Autonomous Systems (ASes) of different types and business objectives. In the Internet ecosystem, traffic flow is (sometimes loosely) coupled with financial exchanges, and routing and peering policies are often dictated by economic and strategic objectives. These ASes interact through transit and peering agreements. Most of these interactions are local in nature, without coordinated control or regulation, but they often have global impact affecting the performance and reliability experienced by users, the financial viability of network and service providers, and to some degree the global economy.
The dynamic nature of the Internet ecosystem, with continual emergence of new applications, large penetration of video streaming, falling transit prices, consolidation of content, geographic expansion of large content sources, new peering schemes with cheap availability of peering infrastructure at Internet Exchange Points (IXPs) etc., renders it too intricate for simple models to capture the complexity of network interactions. This difficulty is exacerbated by the asynchrony and lack of coordination among ASes.
The high-level objective of this thesis is to create a scientific basis for modeling interdomain interconnection and dynamics. Specifically, we aim to understand the structure and dynamics of the Internet ecosystem from an economic perspective, capturing the interactions between network business relations, internetwork topology, routing policies, and the resulting interdomain traffic flow. We expect to make the following concrete contributions through this thesis:
1. GENESIS: A computational agent-based model of interdomain network formation, traffic flow and economics. We aim to show how peering adds instability to an otherwise stable network and how sensitive the network formation process in the Internet is to various factors.
2. An analysis of the gravitation towards Open peering by transit providers observed recently, and its economic consequences.
3. An empirical study of peering behavior of different categories of ASes.
4. A cost-benefit-analysis approach to selection and evaluation of settlement-free peers. This scheme can replace existing broad rule-based peering strategies in the Internet.