Sequence Prediction-based Proactive Caching in Vehicular Content Networks

Abstract

Proactive caching is a promising approach to achieve efficient content delivery, reduce content retrieval latency, and improve user experience in vehicular content networks. This paper proposes a mobility prediction based proactive caching scheme utilizing a sequence prediction algorithm, namely Sequence Prediction-based Proactive Caching, to predict the next possible RSU along a vehicle’s path and pre-locate relevant content. Four systems’ performance is evaluated in two areas of Las Vegas and Manchester. The obtained results in Las Vegas have shown that the proposed system outperforms the other three systems i.e., Baseline Proactive Caching system, non-proactive caching system and no-caching system. It is shown to be up to over three times and twice better than the non-proactive caching system and Baseline Proactive Caching system respectively in terms of cache performance and on average, network delay of SPPC is reduced by 18% and 24% compared with non-proactive caching system and no-caching system respectively. Performance benchmark in Manchester generalized the application of SPPC system and asserted its superiority. The paper also gives insight into solving prediction issues with data mining techniques.