User-Oriented Caching Strategy In Content-Centric Networking

With the rapid development of the Internet and the application of new technologies,great changes have taken place in the role orientation and demand of the network.The network architecture based on host-to-host communication is no longer appropriate,Content-Centric Networking is proposed as Next Generation Network Architecture to solve these problems.Built-in caching is part of CCN Architecture,it can improve the efficiency of content distribution.Cache capacity is limited by node wire speed forwarding requirements,and there are many contents in the network,The performance of the cache strategy determines the efficiency of the cache system.At present,CCN defaults to the Leave Copy everywhere caching strategy,which leads to serious content redundancy.In order to improve the performance of caching system,two caching strategies are proposed from the perspective of user-oriented.Firstly,a cooperative caching strategy based on user preference(CCUP)is proposed for the selective cacheing and optimally placing of the content in CCN.According to the strategy,user's preferences for content type and content popularity are considered as User's local preference indexes to realize the selection of cached.Then,the differentiated caching strategy is executed on the content that needed to be cached,the globally active content is cached at the important central node for content distribution,and the inactive content is cached according to the matching of the local preference and the distance level between node and user.Finally,the near access of user to local preference content and the quick distribution of global active content are both achieved.The simulation results show that,compared with typical caching strategies,the proposed CCUP has obvious advantages in average cache hit rate,hop reduction rate and request delay.Secondly,in order to optimize the replica placement and algorithm overhead in CCN,a Probabilistic Caching Strategy Based on User Requirements and Node State(PCRS)is proposed.According to the time distribution of content request arrived,the concept of user demand acceleration is proposed for the first time,and predicting user demand in combination with content popularity and content demand acceleration.The node determines the content cache probability based on user Requirements and node state.Considering the uncontrollability of probability cache,the algorithm uses cache suggestions to control the redundancy of cache contents,and give a cache replacement method based on user requirements.Finally,the simulation results show that,compared with typical caching strategies,the proposed PCRS has obvious advantages in average cache hit rate,hop reduction rate and request delay.Furthermore,the extra cost of PCRS is relatively small.