A caching strategy based on dynamic popularity for named data networking

Abstract

Named data networking (NDN) is a prominent architecture for the future internet. In NDN, routers have the capacity of in-network cache, which can completely improve network performance. However, the cache capacity in routers is limited and how to utilise the cache resources effectively is still a great challenge. To solve the problem, this study presents a dynamic popularity caching strategy based on additive increase multiplicative decrease for NDN (DPCA). DPCA takes content popularity and caching capacity into account and it utilises AIMD algorithm to adjust the popularity threshold dynamically. At the same time, it also proposes a evict algorithm which takes the historical information of content popularity, the trend of content request and the interval from the last request time into account. The simulation results show that the DPCA strategy can effectively improve cache hit ratio, decrease network throughput and reduce the average hit distance compared with other schemes.