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Department of Computer Science Seminar
2009 Series

Internet Economics and ISP Settlement Problems

Mr. Tianbai Ma
Columbia University

Date: February 6, 2009 (Friday)
Time: 2:30 - 3:30 pm
Venue: RRS628, Sir Run Run Shaw Building, Ho Sin Hang Campus

Internet service providers (ISPs) depend on one another to provide global network services. However, the profit-seeking nature of the ISPs leads to selfish behaviors that result in inefficiencies and disputes in the network. From a micro perspective, this concern manifests in ISP selfish routing strategies and discriminatory interconnections, which limit the stability of routes, balkanize the Internet and deteriorate performance and profit of the network. From a macro perspective, this concern is at the heart of the Network Neutrality debate, which asks for an appropriate compensation structure that satisfies all types of ISPs. In this work, we design a profit-sharing mechanism based on the Shapley value originated from Coalition Game Theory. Under this mechanism, selfish ISPs would yield globally optimal routing and interconnecting decisions, reaching a Nash equilibrium that maximizes network efficiencies. We derive closed-form profit solutions for structured ISP topologies and develop a dynamic programming procedure to calculate solutions for general topologies. Based on these solutions, we draw some implications on the bilateral settlements between ISPs. In practice, these results provide guidelines for ISPs to solve disputes and negotiate stable and incentive settlements and for governments to establish regulatory policies for the Internet industry.

Tianbai Ma received his B.Sc. (first-class honors) in Computer Science in July 2002 and M.Phil. in Computer Science and Engineering in July 2004, both from the Chinese University of Hong Kong. He is currently working toward the Ph.D. degree at Columbia University in the city of New York. His research interests include: Internet Economics, Algorithmic Game Theory & Mechanism Design, Telecommunication Networks, and Stochastic Modeling.

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