Socially Driven Joint Optimization of Communication, Caching, and Computing Resources in Vehicular Networks
Lianming Xu, Zexuan Yang, Huaqing Wu, Yanru Zhang, Yanhui Wang, Li Wang, Zhu Han
Abstract
To support multifarious vehicular applications, content sharing among vehicles or between vehicles and infrastructures can enable efficient service provisioning. In this work, we investigate joint communication, caching, and computing (3C) resource allocation to support efficient content sharing between content providers (CPs) and content requesters (CRs) in vehicular networks. To tackle the high complexity of joint 3C resource allocation, we decouple the problem into a long-term content caching strategy to allocate caching resources plus a method for short-term CP-CR pairing and corresponding communication-computing resource allocation. Specifically, a popularity and social similarity (P-SS) based caching strategy is proposed by incorporating both physical and social information. As selfish CRs may refuse to reveal their quality of service (QoS) requirements to the CPs and lead to the information asymmetry, we adopt contract theory to allocate communication and computing resources for each potential CR-CP pair. We then propose a stable-matching based algorithm to match CPs and CRs for efficient content sharing. Simulation results verify that the proposed scheme can effectively solve the problem with low complexity.