Complexity of Internet Interconnections: Technology, Incentives and Implications for Policy

31 Pages Posted: 22 Jul 2012

See all articles by Peyman Faratin

Peyman Faratin

Massachusetts Institute of Technology (MIT) - Sloan School of Management

David D. Clark

MIT CSAIL

Steven Bauer

Massachusetts Institute of Technology (MIT) - Laboratory for Computer Science (LCS)

William Lehr

Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Date Written: August 15, 2007

Abstract

End-to-End (E2E) packet delivery in the Internet is achieved through a system of interconnections between heterogeneous entities called Autonomous Systems (ASes). As of March 2007, there were over 26,000 in use. Most ASes are ISPs, but they also include enterprises, governmental or educational institutions, and increasingly large content providers with mostly outbound traffic such as Google, Yahoo, and YouTube as well as overlay content distribution networks such as Akamai and Limelight. Each AS controls or administers its own domain of addresses but ASes must physically interconnect to provide end-to-end connectivity across the Internet. Interconnection is not only important from a reachability perspective but also quality and performance perspective, because how ASes interconnect, both physically and contractually, determines how packets are routed and impacts the quality and choice of services that may be supported.

The initial pattern of AS interconnection in the Internet was relatively simple, involving mainly ISPs with a balanced mixture of inbound and outbound traffic. One goal of this paper is to demonstrate how changing market conditions and industrial organization of Internet have jointly forced interconnections and associated contracts to become significantly more diverse and complex than is commonly understood. The diversity of interconnection contracts is significant because efficient allocation of costs and revenues across the Internet value chain impacts the profitability of the industry. However, current models of interconnection fail to reflect such emerging diversity of possible interconnections. We currently lack good data and models on these developments. In particular, most models of AS interconnection describe two sorts of arrangements: transit (a “vertical” relationship where small networks pay larger network for access to the rest of the Internet) and peering (a “horizontal” relationship where similar sized networks engage in revenue-neutral interconnection). We will highlight the now obvious distinction between networks that specialize in content distribution and broadband residential networks that specialize in consumer access to the Internet. The introduction of such ASes increases the heterogeneity of players in the interconnection market. Furthermore, their highly asymmetric pattern of traffic flow (from content to “eyeballs”) has resulted in increased complexity of the incentives to interconnect, and the diversity of the resulting negotiation.

Not surprisingly, the challenges of recovering the fixed and usage-sensitive costs of network transport have given rise to more complex settlements mechanisms than the simple bifurcated (transit and peering) model. In the following, we provide an insight to recent operational developments, explaining why interconnection in the Internet has become more complex, the nature of interconnection bargaining process, the implications for cost/revenue allocation and hence interconnections incentives, and what this means for public policy.

Suggested Citation

Faratin, Peyman and Clark, David D. and Bauer, Steven and Lehr, William, Complexity of Internet Interconnections: Technology, Incentives and Implications for Policy (August 15, 2007). TRC 2007. Available at SSRN: https://ssrn.com/abstract=2115242

Peyman Faratin (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
E62-416
Cambridge, MA 02142
United States

David D. Clark

MIT CSAIL ( email )

Stata Center
Cambridge, MA 02142
United States
617-253-6003 (Phone)

Steven Bauer

Massachusetts Institute of Technology (MIT) - Laboratory for Computer Science (LCS) ( email )

United States

William Lehr

Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL) ( email )

Stata Center
Cambridge, MA 02142
United States

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