Online Pricing-based Content Cache Trading for Multi-Provider Vehicular Networks
Haowei Chen, Shuiguang Deng, Hongze Zhu, Cheng Zhang · 2022
Edge caching has emerged as a prominent paradigm for supporting the needs of contents by pushing storage functionalities to ratio access network (RAN) and alleviates the strain of core network. However, current mainstream small base station (SBS) caching can not adapt to system dynamics due to fixed infrastructures. Mobile network operators (MNOs) attempt to explore the potential of vehicles as content carries to cope with time-varied and location-based demands resulted by mobile environment and improve both of hit rate and QoS (delivery rate) for users’ file requests. Nevertheless, vehicular caching trading policy between MNO and content providers (CPs) arriving in unknown sequence still remains complicated to design since selfish and private CPs may be vicious to contend for limited vehicular capacity to obtain larger profits. To bridge this gap and provide economic insights into vehicular caching, we focus on caching leasing between MNO and CPs and propose a general cache valuation and online pricing framework to realize incentive compatibility, individual rationality, privacy protection and computational efficiency with the target of social welfare maximization. To the best of our knowledge, this is the first work to study the cache trading pattern of vehicular networks. Experimental results based on the ONE simulator substantiate the usefulness and superiority of our scheme in term of social welfare maximization.