A recursive estimation of network state for improving probabilistic caching

Abstract

There is a trend to introduce content caches as an inherent capacity of network device, such as routers, for improving the efficiency of content distribution and reducing network traffic. In this paper, we discuss the network state estimation in probabilistic caching based on a study with Bayesian inference, and propose a recursive estimation method for potentially improving the performance of adaptation to time-varying network state.

Compound Popular Content Caching Strategy in Named Data Networking

“…The TimesIn factor is used to calculate the specific duration taken for the content to be cached. ProbCache increases the tendency of content caching near the consumer using the TimesIn factor and it increases the duration for a content to be cached at those routers, which are closer to the consumers [44]. Therefore, probabilistic caching decision is derived after the calculation of two factors (TimesIn and CacheWeight) as given below.…”