Hierarchical Matching with Peer Effect for Latency-Aware Caching in Social IoT

The Internet of Things (IoT) promises to be a source of great benefits to users, operators and manufactures in different application scenarios. To allow smart objects to have their own social networks and share contents via device-to-device (D2D) communications in the IoT, the combined social IoT can potentially provide information and services more efficiently. This paper focuses on the latency optimization in the social IoT with D2D based caching. To achieve the optimization object, we formulate the combinatorial problem as a hierarchical matching game, which can be decoupled into a content sharing problem and a resource allocation problem. For solving the content sharing problem, a one-to-one stable matching algorithm is proposed by considering both social and physical characteristics. As for the resource allocation, we model this problem as a many-to-one matching with peer effect and propose a distributed algorithm to achieve a two-sided exchange-stable matching. In this way, the combinatorial problem can be solved by the proposed hierarchical stable matching algorithm. Simulation results show that our proposed algorithms are stable, converging and are capable of offering a better performance than other benchmarks.