On the architecture of a clustering platform for the analysis of big volumes of data
Ioan-Daniel Borlea, Radu‐Emil Precup, Florin Drăgan · 2016
In the last years the volume of data that was generated by the mankind has increased and the complexity of data generated has also increased. Since the computers have evolved and provide more processing power, it is possible to carry out the real-time analysis of big volumes of data. This paper suggests the architecture of a big data processing platform called BigTim, which is able to run clustering algorithms on Windows operating systems. The platform will allow running clustering algorithms in a parallelized manner using the advantage that the entire processing power of a multi-core computer.