MapReduce Model: A Paradigm for Large Data Processing
Kabiru D. Ibrahim, Ibrahim M. M, Yusuf M. Y. Idris, Adamu Bello, Kassim S. A · Zenodo (CERN European Organization for Nuclear Research) · 2023
MapReduce is a programming paradigm that enables massive processing of large amount of data over several machines in a cluster of commodity computers. It is fault tolerant and scalable hence suitable for cloud computing applications. This paper come up with a second order nonlinear model of the MapReduce using experimental data collected from Grid5000 experimental tested accessed from the local machine using Linux Secure Socket Shell protocol (SSH) as a command line interphase. System identification was performed on the collected data using MATLAB toolbox. The nonlinear model obtained was linearized and discretized using numeric optimization techniques to obtain the continuous transfer function. Within the limits of operating points, the model shows a perfect tracking and good representation of the dynamics of the real system and hence can be suitable for applying control laws.