A Simple Computational Market for Network Information Services

Visionary projections of a wide-axea network teeming with intelligent agents describe an environment where end-users and their agents can pick and choose among a great vaxiety of potentially valuable information services. However, neither network capabilities nor users’ time and money axe infinite. Computational markets provide one type of mechanism for ~llocating limited resources in such an environment in a distributed, dynamic way. Moreover, the underlying economic theory provides an analytical framework for predicting aggregate behavior and designing individual agents. In this paper, we describe a prototypical computational maxket model for information services distributed over a network. Our initial focus is on the economic problem of when and where to establish mirror sites for the more popular information services. Competitive agents choose to set up mirrors based on going prices for network bandwidth, computational resources, and the information service. Depending on the experimental setup, we observed a range of qualitative behaviors.