一种基于节点中心性近似算法的ICN协作缓存策略

An ICN Cooperative Cache Strategy Based on Node Centrality Approximation Algorithm

为了降低信息中心网络(Information Centric Networking,ICN)缓存冗余度和平均接入代价,提出一种基于节点中心性度量近似算法的协作缓存策略Centrality Metric Approximation Algorithm(CMAA)。考虑到精确计算最短路径的工作量对缓存性能的影响,CMAA策略利用最短路径近似估计值以提高节点中心性的计算效率,将节点中心性近似度量加权融合值、节点热度和缓存利用率三者作为缓存影响因子,计算得出兴趣包转发路径各节点的缓存优先级。在多种实验条件下对CMAA进行仿真实验,结果表明与LCE(Leave Copy Everywhere)和CLFM(Cache“Less for More”)相比,CMAA在平均缓存请求时延变化不大的情况下,可有效地提高缓存命中率,降低平均接入代价,从而改善缓存系统性能。

In order to reduce the cache redundancy and average access cost of information centric networking(ICN),a collaborative cache strategy based on node centrality metric approximation algorithm(CMAA)is proposed.Considering the impact of the workload of accurately calculating the shortest path on the cache performance,CMAA uses the approximate estimation of the shortest path to improve the calculation efficiency of node centrality,and takes the weighted fusion value of the approximate measurement of node centrality,node heat and cache utilization rate as the cache impact factors to calculate the cache priority of each node in the interest packet forwarding path.The simulation results of CMAA under various experimental conditions show that compared with LCE(leave copy everywhere)and CLFM(cache“less for more”),CMAA can effectively improve the cache hit rate,reduce the average access cost and improve the performance of the cache system with little change in the average cache request delay.