Secure Budget-Aware Edge Caching in Mobile Social Networks: A Dynamic Optimization Approach

The rapid rise of mobile social networks (MSNs) demands low-latency content delivery, making edge caching crucial for enhancing user experience. As caching content consumes valuable and limited resources, it is essential to implement efficient allocation methods that optimize all entities’ utilities. However, many resource allocation approaches are computationally and communicationally intensive, and they also overlook real-world issues like selfish edge caching devices (EDs) manipulating content metrics and the need for practical, constraint-aware strategies. To address these challenges, we propose a secure edge caching architecture for MSNs. This framework employs a Stackelberg game, where the content provider (CP) with budget constraints, as the leader, determines the payment strategy, and the EDs, as followers, decide on service quality. To overcome dynamic network uncertainties and for the lack of knowledge on interactions between the CP and EDs, we employ a centralized technique for efficient ED parameter estimation, solving the CP optimization problem with minimal communication and high accuracy. Additionally, we integrate a secure content popularity computation scheme to protect content metrics from manipulation, enhancing trustworthiness in content delivery. Simulation results show that our framework achieves at least 500-fold reduction in communication overhead compared to a state-of-the-art method, while also improving caching efficiency and security, providing a robust solution for modern MSNs.