Distributed Probabilistic Caching strategy in VANETs through Named Data Networking

Abstract

Named Data Networking (NDN) has natural advantages to greatly overcome the challenges such as rapidly changing topology, short-lived and intermittent connectivity in Vehicular Ad hoc Networks (VANETs), owing to its name-based routing and in-network caching characteristics. However, the caching strategy in the Vehicular NDN, AlwaysCache, in which nodes will cache all solicited contents received or overheard, may waste resources and reduce the cache efficiency. This paper presents a Distributed Probabilistic Caching (DPC) strategy in Vehicular Ad hoc Networks (VANETs) through Named Data Networking (NDN). In DPC, the caching decisions are taken by each node separately and independently. The nodes take decisions considering users' demands mined from collected interest entries, the vehicle's importance obtained from the analysis of the Degree Centrality and the Betweenness Centrality in the ego network, and relative movement of the receiver and the sender. Simulation results from ndnSIM network simulator demonstrate that DPC is superior to AlwaysCache and P(0.5) strategy in cache hit ratio, hop count and delay. In addition, DPC improves the caching efficiency and the content diversity in the network.