Decentralized Edge Caching under Budget and Storage Constraints: A Game-Theoretic Approach

TL;DR

This paper models decentralized edge caching among multiple content providers and edge devices as a hierarchical game, analyzing equilibrium existence, convergence, and economic impacts under storage and budget constraints.

Contribution

It introduces a game-theoretic framework combining Stackelberg and non-cooperative games to analyze resource allocation in multi-CP edge caching systems.

Findings

CP competition forms an exact potential game under light storage constraints.

Simulations show stable convergence regardless of infrastructure scale.

Storage scarcity increases inequality among CPs and bargaining power of EDs.

Abstract

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.