命名数据网络中基于数据请求代价与流行度的动态替换策略

针对怎样高效地对命名数据网络(NDN)缓存中的数据进行替换的问题,提出了一种综合考虑数据流行度与数据请求代价的数据替换策略。该策略根据数据的请求时间间隔动态地分配数据流行度因子与数据请求代价因子的比重,使节点缓存高流行度与高请求代价的数据。当用户下次请求数据时能够从本节点获取,降低数据请求的响应时间并减少链路拥塞。仿真结果表明,本策略能够有效提高网内存储命中率,降低用户获取数据的时间以及缩短用户获取数据的距离。

Dynamical replacement policy based on cost and popularity in named data networking

In view of the problem that data for Named Data Networking (NDN) cache is replaced efficiently, a new replacement policy that considered popularity and request cost of data was proposed in this paper. It dynamically allocated proportion of popularity factor and request cost factor according to the interval time between the two requests of the same data. Therefore, nodes would cache data with high popularity and request cost. Users could get data from local node when requesting data next time, so it could reduce the response time of data request and reduce link congestion. The simulation results show that the proposed replacement policy can efficiently improve the in-network hit rate, reduce the delay and distance for users to fetch data.