Performance evaluation of caching placement algorithms in named data network for video on demand service

The purpose of this study is to evaluate the performance of caching placement algorithms
(LCD, LCE, Prob, Pprob, Cross, Centrality, and Rand) in Named Data Network (NDN) for Video on Demand (VoD). This study aims to increment the service quality and to decrement the time of download. There are two stages of activities resulted in the outcome of the study: The first is to determine the causes of delay performance
in NDN cache algorithms used in VoD workload. The second activity is the evaluation of the seven cache placement algorithms on the cloud of video content in terms of the key performance metrics: delay time, average cache hit ratio, total reduction in the network footprint, and reduction in load. The NS3 simulations and the Internet2 topology were used to evaluate and analyze the findings of each algorithm, and to compare the results based on cache sizes: 1GB, 10GB, 100GB, and 1TB. This study proves that the different user requests of online videos would lead to delay in network performance. In addition to that the delay also caused by the high increment of video
requests. Also, the outcomes led to conclude that the increase in cache capacity leads
to make the placement algorithms have a significant increase in the average cache hit
ratio, a reduction in server load, and the total reduction in network footprint, which resulted in obtaining a minimized delay time. In addition to that, a conclusion was made
that Centrality is the worst cache placement algorithm based on the results obtained.