Cooperative Caching Optimization Strategy Based on Hedonic Game Theory in Mobile Edge Computing
Abstract
To address the problems of limited caching resources at edge nodes, dynamically changing user requests, and imbalanced node loads in mobile edge computing, this paper proposes a hedonic-game-based cooperative caching optimization strategy (HG-CC). First, a joint utility function integrating caching benefit and cooperation cost is constructed by considering content popularity, node resource status, network distance, cache complementarity, and cooperation cost. Second, the caching cooperation relationship among edge nodes is modeled as a hedonic game, enabling nodes to autonomously select cooperative coalitions according to their own utilities and form a stable coalition partition. Finally, a differentiated content deployment strategy is adopted within each coalition to reduce redundant caching and improve content coverage and cache resource utilization. Simulation and real-world request trace experiments demonstrate that, compared with the local most popular caching strategy and the fixed-neighbor cooperative caching strategy, the proposed method improves the cache hit ratio while reducing the average service latency and node load variance. It also exhibits good robustness against content popularity prediction errors, validating its effectiveness and adaptability.