The rapid growth of mobile social networks (MSNs) has significantly increased the demand for low-latency and reliable content delivery, motivating the deployment of edge caching systems. In practice, multiple content providers (CPs) compete for the limited storage resources of edge devices (EDs), while facing heterogeneous budgets and operational costs. This paper investigates a decentralized multi-CP edge caching framework that jointly accounts for CP budget constraints, ED storage limitations, and strategic interactions among all entities. We formulate the interaction between CPs and EDs as a hierarchical game, combining a Stackelberg model for CP-ED interactions with a non-cooperative game among competing CPs. Under light storage constraints, we show that CP competition constitutes an exact potential game, ensuring the existence of a pure-strategy Nash equilibrium and enabling decentralized convergence. When storage constraints are binding, the resulting game loses this structure; nevertheless, extensive simulations demonstrate stable and efficient convergence in practice. Through a comprehensive numerical evaluation, we show that convergence behavior is primarily driven by CP competition rather than the scale of edge infrastructure. We further reveal that storage scarcity fundamentally alters economic outcomes, amplifying inequality among CPs while increasing the relative bargaining power of EDs. The proposed framework provides a scalable and economically grounded solution for decentralized resource allocation in multi-provider edge caching systems.

翻译：移动社交网络的快速发展显著提升了对低延迟与高可靠内容交付的需求，推动了边缘缓存系统的部署。实践中，多个内容提供商为竞争边缘设备的有限存储资源展开博弈，同时面临异质性的预算与运营成本。本文研究了一个去中心化的多内容提供商边缘缓存框架，该框架联合考虑了内容提供商的预算约束、边缘设备的存储限制以及所有实体间的策略交互。我们将内容提供商与边缘设备间的交互建模为层次化博弈，融合了用于描述二者交互的斯塔克伯格模型与竞争性内容提供商之间的非合作博弈模型。在轻量存储约束下，我们证明内容提供商之间的竞争构成精确势博弈，确保纯策略纳什均衡的存在性并实现去中心化收敛。当存储约束严格生效时，博弈结构丧失上述特性，但大规模仿真表明实际场景中仍能实现稳定高效的收敛。通过全面的数值评估，我们发现收敛行为主要由内容提供商之间的竞争驱动，而非边缘基础设施的规模。进一步研究表明，存储稀缺会根本性地改变经济结果：在加剧内容提供商间不平等的同时，提升边缘设备的相对议价能力。所提框架为多提供商边缘缓存系统中的去中心化资源分配提供了可扩展且具有经济理论支撑的解决方案。