Machine Learning on Named Data Network: A survey Routing and Forwarding Strategy

Abstract

NDN, a data-centric network which can reduce the load on the network (especially on the server side) is widely developed using Machine Learning (ML) recently. The main reason is the capability of ML to examine a huge data, for example in FIB. In FIB, to identify the longest prefix is expensive and hard to operate without precise optimization. The goal of this study is to serve as guidelines for future research by conducting surveys on current NDN development with ML, especially for routing and forwarding classification.