# A Literature Review on Caching Transient Contents in Vehicular Named Data Networking
## 5 To Cache and Replace Transient Contents in VNDN
### Caching Policies  
The simplest caching scheme for VNDN conceived for transient contents is deployed in Reference [41]. The strategy, called Freshness-Driven Caching (FDC), distinguishes between short- and long- lasting contents and varies the caching probability depending on the residual lifetime (RL) of the received Data packet. The RL parameter of a packet \(d_{k}\) is computed by considering the FreshnessPeriod, the timestamp (additionally included by the source to avoid cache inconsistency) and the time instant \(t\) when the packet \(d_{k}\) is received, as follows: \(RL(d_{k})=timestamp(d_{k})+FeshnessPeriod(d_{k})-t\). If \(RL(d_{k})<0\) the packet is expired. A dynamic threshold \(Th\), used to distinguish long- or short-lasting contents, is obtained as the exponential weighted moving average (EWMA) of the residual lifetimes carried by the received packets. If the residual lifetime \(RL(d_{k})\) is greater than the threshold, the packet is cached with probability \(p=1\); otherwise, it is cached with probability \(p=\frac{RL(d_{k})}{Th}\). The rationale behind the strategy is that, in presence of a uniform traffic distribution, as it would be in the case of some vehicular traffic, long-lasting contents have a higher chance to be requested during their lifetime. Therefore, long-lasting contents are always cached, while short-lasting contents are cached with a lower probability that tends to zero if the residual lifetime is going to expire. The work in Reference [51], instead, defines a caching mechanism for RSUs only, based on service latency and content freshness. The authors clarify that the service latency shows how fast users get the contents after raising a request, while the freshness shows if the result is updated or not. The two factors are conflicting: to guarantee high data freshness requires frequent data exchanges that, in turn, create network congestion and increase the service latency. The proposed scheme, called Cache-Assisted Lazy Update and Delivery (CALUD), aims at balancing three factors: content update, delivery, and radio resource allocation. A Time Division Multiple Access (TDMA) scheme is implemented,where the RSU takes into account the received content requests and accommodates them in a First-In-First-Out (FIFO) fashion. To serve more users requesting the same information, downlink broadcast transmissions are used. When vehicular contents are characterized by a skewed popularity distribution, like many Internet contents, popularity becomes an important caching decision metric that should be taken into account. Some works apply popularity-based caching at infrastructure nodes only, e.g., RSUs [52], while many others assume that also vehicles are able to estimate the popularity of contents, although the latter may largely change with the position of the nodes (i.e., vehicular contents have usually a specific geographical relevance) [53]. However, it is worth observing that, in presence of transient contents, the popularity metric should be matched with the lifetime information: caching contents that are going to expire immediately could be useless, and it may also force a high number of replacement operations. This observation is taken into account by the Diversity-improved cAchiNg of popular Transient contEnts (DANTE) strategy in Reference [54], which defines a composite decision metric based on three content parameters, namely popularity, residual lifetime, and availability, as autonomously perceived by the vehicles in their neighborhood. A first target is to cache with high probability the popular long-lasting contents, which can likely serve more requests during their lifetime. Therefore, each vehicle maintains information of request rate and freshness of received contents. At the same time, however, DANTE aims to improve the cache diversity (and minimize the redundancy) by reducing the caching probability if contents are already available in the local neighborhood.