Mining Distributed Data Streams on Content Delivery Networks
Eugenio Cesario, Carlo Mastroianni, Domenico Talia · 2014
Mining data streams (DSs) is a very important research topic and has recently attracted a lot of attention, because in many cases data is generated by external sources so rapidly that it may become impossible to store it and analyze it offline. This chapter elaborates a distributed architecture for mining DSs generated from multiple and heterogeneous data sources, with specific focus on the case of content delivery networks. Beyond presenting the architecture, the chapter describes an implemented prototype and discusses a set of experiments performed in a distributed environment composed of two domains each one handling a DS. A very promising avenue could be to devise hybrid approaches, which try to combine the best of single-and multiple-pass algorithms. A strategy of this kind is adopted in the mining architecture presented in the chapter.