International audience—In this paper, we address the caching problem in small cell networks from a game theoretic point of view. In particular, we formulate the caching problem as a many-to-many matching game between small base stations and service providers' servers. The servers store a set of videos and aim to cache these videos at the small base stations in order to reduce the experienced delay by the end-users. On the other hand, small base stations cache the videos according to their local popularity, so as to reduce the load on the backhaul links. We propose a new matching algorithm for the many-to-many problem and prove that it reaches a pairwise stable outcome. Simulation results show that the number of satisfied requests by the small base stations in the proposed caching algorithm can reach up to three times the satisfaction of a random caching policy. Moreover, the expected download time of all the videos can be reduced significantly. I. INTRODUCTION During the last decade, the rapid proliferation of smart-phones coupled with the rising popularity of Online Social Networks (OSNs) have led to an exponential growth of mobile video traffic [1]. Meanwhile, existing wireless networks have already reached their capacity limits, especially during peak hours [2]. In order to ensure acceptable Quality of Experience (QoE) for the end-users, the next generation of wireless net-works will consist of a very dense deployment of low-cost and low-power small base stations (SBSs) [3]. The SBSs provide a cost-effective way to offload traffic from the main macro-cellular networks. However, the prospective performance gains expected from SBS deployment will be limited by capacity-limited and possibly heterogeneous backhaul links that connect the SBSs to the core network [3]. Indeed, the solution of deploying high speed fiber-optic backhaul is too expensive and thus, the use of DSL backhaul connections need to be considered [4]. Distributed caching at the network edge is considered as a promising solution to deal with the backhaul bottleneck [5], [6]. The basic idea is to duplicate and store the data at the SBSs side. Consequently, users' requests can be served locally, from the closest SBSs without using the backhaul links, when possible. In prior works, the cache placement problem has been mainly addressed for wired networks, especially for Content Delivery Networks (CDNs) [7]–[10]. However, the CDNs topology is different from the small cell networks topology since the CDNs' caching servers are part of the core network while the SBSs are connected to the core network and the User Equipments (UE) via backhaul and radio links, respectively. Hence, it is necessary to explore new cach

Abstract-In this paper, an incentive proactive cache mechanism in cache-enabled small cell networks (SCNs) is proposed, in order to motivate the content providers (CPs) to participate in the caching procedure. A network composed of a single mobile network operator (MNO) and multiple CPs is considered. The MNO aims to define the price it charges the CPs to maximize its revenue while the CPs compete to determine the number of files they cache at the MNO's small base stations (SBSs) to improve the quality of service (QoS) of their users. This problem is formulated as a Stackelberg game where a single MNO is considered as the leader and the multiple CPs willing to cache files are the followers. The followers game is modeled as a noncooperative game and both the existence and uniqueness of a Nash equilibrium (NE) are proved. The closed-form expression of the NE which corresponds to the amount of storage each CP requests from the MNO is derived. An optimization problem is formulated at the MNO side to determine the optimal price that the MNO should charge the CPs. Simulation results show that at the equilibrium, the MNO and CPs can all achieve a utility that is up to 50% higher than the cases in which the prices and storage quantities are requested arbitrarily.

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In this paper, the problem of distributed caching in dense wireless small cell networks (SCNs) is studied using mean eld games (MFGs). In the considered SCN, small base stations (SBSs) are equipped with data storage units and cooperate to serve users' requests either from les cached in the storage or directly from the capacity-limited backhaul. The aim of the SBSs is to de ne a caching policy that reduces the load on the capacitylimited backhaul links. This cache control problem is formulated as a stochastic di erential game (SDG). In this game, each SBS takes into consideration the storage state of the other SBSs to decide on the fraction of content it should cache. To solve this problem, the formulated SDG is reduced to an MFG by considering an ultradense network of SBSs in which the existence and uniqueness of the mean-eld equilibrium is shown to be guaranteed. Simulation results show that this framework allows an e cient use of the available storage space at the SBSs while properly tracking the les' popularity. The results also show that, compared to a baseline model in which SBSs are not aware of the instantaneous system state, the proposed framework increases the number of served les from the SBSs by more than 69%.