MapReduce Model: A Paradigm for Large Data Processing
Authors/Creators
- 1. Department of Computer Engineering, school of technology Kano State Polytechnic, Nigeria
- 2. Department of Electrical Engineering, school of technology Kano State Polytechnic, Nigeria
Description
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.