Abstract
An essential aspect of the network paradigm called Named Data Networking (NDN) is that all nodes in the network have the ability to cache contents natively. The focus of this work relies on efficiently choosing which content should be removed from a full cache to allow storing another one. We propose a new caching replacement algorithm for NDN networks called Name Popularity Algorithm (NPA). The proposed algorithm adopts an extra table that takes into account a long time history for the popularity of contents. Thus, when a data content is removed from the cache, its popularity is not reset, improving the cache usage of the network routers. The performance of NPA is compared to well-known strategies in the literature through NS-3/ndnSIM simulations. The results indicate that the proposed algorithm overcomes others with lower end-to-end delay, higher cache hit ratio and smaller hop count. Besides, our code is available as open source to be accessible for other researchers and to allow reproduction of the results.
Highlights
IntroductionD UE to the growing demand for multimedia content, forecasts indicate that approximately 78% of the traffic in mobile networks will come from video applications by 2021, while in 2016 it already represented 60% of mobile traffic [1]
D UE to the growing demand for multimedia content, forecasts indicate that approximately 78% of the traffic in mobile networks will come from video applications by 2021, while in 2016 it already represented 60% of mobile traffic [1].To deal with this significant amount of media content it is essential to create distributed caches as close as possible to end-users [2]
We conducted extensive simulations using the NS-3 discrete simulator through an Named Data Networking (NDN) networking module known as ndnSIM version 2.2
Summary
D UE to the growing demand for multimedia content, forecasts indicate that approximately 78% of the traffic in mobile networks will come from video applications by 2021, while in 2016 it already represented 60% of mobile traffic [1] To deal with this significant amount of media content it is essential to create distributed caches as close as possible to end-users [2]. With the Internet evolution, new demands for the network emerged, such as support for scalable distribution of content, mobility and security, among others [4]. These demands have motivated the scientific community to investigate alternative architectures for the Internet of the future.
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