Congestion-Aware Modeling and Analysis of Sponsored Data Plan from End User Perspective

Abstract

The past decade has witnessed the rapid expansion of demands for mobile traffic, while the traditional mobile traffic pricing schemes cannot accommodate such demands. Sponsored data plan (SDP), which can increase the revenue of all stakeholders in the market through transferring some of the revenue from content providers (CPs) to end users (EUs), is more suitable. However, existing studies have focused more on Internet service providers (ISPs) and CPs, ignoring the influence of EUs (e.g., the inherent attribute differences of EUs and the interaction among EUs) on the market under SDP. Regarding the difficulty of modeling the abstract property about interaction among EUs, we utilize network congestion as the medium and construct the congestion-aware SDP model based on Stackelberg game. The newly proposed model can not only analyze how network congestion affects SDP mechanism, but also elucidate the impact of interactions among EUs. More specifically, through theoretical analysis, we prove that there is a unique dynamic equilibrium in the interaction among EUs (i.e., the traffic consumption of different EUs). By taking into account network congestion, the newly proposed model also more accurately and realistically describes the optimal strategies and computation methods of all stakeholders in the market. Moreover, simulation experiments demonstrate that the positive effect brought by SDP is not as obvious as before, and EUs influence each other instead of being independent of each other. Overall, this paper emphasizes the non-negligible influence of EUs and promotes a deeper understanding of SDP mechanism, which can guide the relevant stakeholders to optimize their own decision-making details.