Joint Pricing and Cache Placement for Video Caching: A Game Theoretic Approach

Abstract

Caching can effectively smooth the temporal traffic variability and decrease the redundant data transmission in mobile video delivery. In this paper, we consider a video caching system consisting of a video provider (VP), a mobile network operator (MNO) with a set of cache-enabled base stations (BSs), and multiple mobile users. The VP leases some popular videos to the MNO, while the MNO places these rented videos in local caches of its BSs to save expensive backhaul transmission cost. However, in such a two-sided market, these two entities are competing with each other for their own profit due to their opposite expectation on the video pricing. To address this, we model the competition between the two entities using the framework of Stackelberg games and propose a joint video pricing and cache placement strategy by considering the heterogeneity of video file sizes and exploiting the classic law of demand from the field of economics. The proposed optimization problem is able to jointly maximize the profit of the VP and the MNO by the optimal selection of the video pricing and the cache placement strategy given that price, for both noncooperative BS caching and cooperative BS caching cases. We then develop iterative algorithms based on dynamic programming and gradient ascent, respectively, for these two cases to find the Stackelberg equilibrium (SE). The simulation results further show that the proposed joint optimization formulation follows the law of demand in economics, and the proposed algorithms for both cases can efficiently converge to the SE point that jointly maximizes the profit for both the VP and the MNO.