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Charging different prices for Internet access at different times induces users to spread out their capacity, or bandwidth, g consumption across times of the day. Is it feasible and how much benefit can it bring? The authors design architecture for time-dependent broadband pricing. They develop an efficient way to compute the cost-minimizing time-dependent prices for an Internet Service Provider (ISP), using both a static session-level model and a dynamic session model with stochastic arrivals. Their formulations of the optimization problem remain computationally tractable on a large scale. They show simulations illustrating the use and limitations of time-dependent pricing, and discuss next steps in implementing and deploying the theory in the TUBE Project.
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