车联网场景下基于内容中心网络的优化缓存策略

Optimized Caching Strategy Based on Content Centric Networking in Internet of Vehicles

车联网中,如何有效选择缓存位置和缓存内容对于提高整体网络性能至关重要。针对上述问题,引入了内容中心网络技术,提出了一种新的优化缓存策略——缓存位置和缓存内容的选择取决于车辆节点值和内容流行度(Vehicle Node Value and Content Popularity,VNVCP)。首先,定义了连通性、中间中心性和特征向量中心性3个车辆节点属性用来评估车辆节点的值,具有不同值的车辆节点缓存具有不同流行度的内容,内容的重要性由其受欢迎程度决定。其次,该策略利用不同类型内容受欢迎程度的差异确保缓存内容分布均匀,同时评估来自多个属性的车辆节点的值以提高车辆节点利用率。仿真结果表明,VNVCP在缓存命中率、平均跳数和传输延迟方面明显优于传统的LCE(Leave Copy Every where)、Prob(0.5)和MPC(Most Popular Content)。

In Internet of Vehicles(IoT),how to effectively select the cache location and content is very important for improving the overall network performance.To solve the above problems,the Content Centric Networking(CCN)technology is introduced and a new optimized caching strategy is proposed.The selection of cache location and cache content depends on Vehicle Node Value and Content Popularity(VNVCP).Firstly,three vehicle node attributes about connectivity,betweenness centrality and eigenvector centrality are defined to evaluate the vehicle node values.The vehicle nodes with different values cache the content with different popularity.The importance of content is determined by its popularity.Secondly,the proposed strategy utilizes the popularity differences of different types of content to ensure uniform distribution of cached content,and evaluates the values of vehicle nodes from multiple attributes to improve the utilization of vehicle nodes.The simulation results show that the proposed VNVCP is significantly better than traditional Leave Copy Everywhere(LCE),Prob(0.5)and Most Popular Content(MPC)in cache hit rate,average hop count and transmission delay.