Decentralized Edge Caching under Budget and Storage Constraints: A Game-Theoretic Approach
2026-05-05 • Computer Science and Game Theory
Computer Science and Game TheoryPerformance
AI summaryⓘ
The authors study how multiple content providers compete to store their content on limited space at network edges to deliver data faster to users. They model this competition as a game where providers and edge devices interact strategically, showing that when storage is plentiful, stable outcomes exist and can be found in a decentralized way. When storage is tight, the problem becomes more complex, but their simulations still find stable results. They also find that limited storage increases inequality between providers and strengthens the position of edge device owners. Overall, the authors propose a practical way to allocate edge storage fairly among competing providers.
mobile social networksedge cachingcontent providersedge devicesStackelberg gameNash equilibriumpotential gameresource allocationdecentralized convergencestorage constraints
Authors
Hamta Sedghani, Zahra Seyedi, Mauro Passacantando, Danilo Ardagna
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.