Time-Dependent Pricing for Multimedia Data Traffic: Analysis, Systems, and Trials

Abstract

The explosive growth of multimedia data traffic in wired and wireless networks have led Internet service providers (ISPs) to use penalty mechanisms like throttling, capping, overage fees to manage network congestion; however, such measures are harmful to the Internet ecosystem. Therefore, we use ideas from economics to create incentive-based, as opposed to penalty-based, solutions for data plans. In particular, we explore time-dependent pricing (TDP) - a form of dynamic pricing that manages congestion by offering time-varying discounts to incentivize users to shift some data traffic temporally. To realize TDP data plans in practice, we provide (i) an optimization model to compute time-dependent prices, (ii) a system implementation for deployment in operational networks, and (iii) experiments with two cellular networks for demonstrating feasibility. Our results show that the users respond to such pricing plans by using higher volume of traffic in lower-priced (off-peak) periods and benefit from a lower $/GB fee, while the ISPs benefit from a higher revenue due to increase in off-peak usage and lower peak-to-average traffic ratio in their network. This suggests that such a pricing solution can incentivize users to modify their usage behavior and enable better revenue management in multimedia-rich networks.