Named data networking is one of the recommended {\color{red}architectures} for the future of the Internet. In this communication architecture, the content name is used instead of the IP address. To achieve this purpose, a new data structure is added to the nodes of named data networking which is called Pending Interest Table (PIT). Scalability, memory consumption, and integration are the significant challenges in PIT design {\color{red} as} it needs to be updated for each packet, and it saves the name of the packet. This paper introduces a new data structure for PIT called DiCuPIT. DiCuPIT is a distributed data structure for the PIT table, {\color{red} that works} based on the Cuckoo filter and can cover the three features as above-mentioned. {\color{red} By} implementing this PIT, {\color{red} the lookup} time shows {\color{red} a 36\% reduction} compared to the methods based on the Bloom filter and 40\% based on hash tables. Moreover, the memory consumption is reduced by 68\% compared to the hash tables-based mechanisms and 31\% compared to the methods based on the Bloom filter.

翻译：命名数据网络是未来互联网推荐架构之一。在此通信架构中，使用内容名称替代IP地址。为实现此目的，命名数据网络节点中新增了一种称为待定兴趣表（PIT）的数据结构。由于每个数据包均需更新PIT且需保存数据包名称，可扩展性、内存消耗与集成性成为PIT设计中的主要挑战。本文提出一种名为DiCuPIT的新型PIT数据结构。DiCuPIT是基于布谷鸟过滤器的分布式PIT表数据结构，能够覆盖上述三项特性。通过实现该PIT，查询时间相比基于布隆过滤器的方法降低36%，相比基于哈希表的方法降低40%。此外，内存消耗较基于哈希表的机制减少68%，较基于布隆过滤器的方法减少31%。