Visualization of Information Theoretic Maximum Entropy Model in Real Time Distributed System

There are various states of affairs in Natural Language Processing (NLP), Thermodynamics and Image processing, which illustrates the maximum entropy model (MEM) at different levels. An application of the principle of maximum entropy for approximation of fundamental probability distribution can depend on the variables that used for recitation of system. In Real Time Distributed System (RTDS) arrival time, worst-case execution time and deadline are some fundamental attributes of real time tasks that elucidate the activities of entire system. As we all know that for the acceptance test (in real time scheduling algorithms) of task scheduling and in order to govern the dynamics (task migration and duplication), utilization is the only parameter that brings into play in RTDS. All these methodologies need current utilization value (=1) of all participant processors of the system. To the best of our knowledge, this paper first time introduces one more contender that promises great affinity to replace utilization factor. This paper introduces MEM in RTDS arena that works analogous to the utilization factor with some additional advantages in terms of scalability and processor information. With the help of some mathematical derivations and theoretical examples, we would like to broadcast that entropy can be another parameter that is able to govern the dynamics in RTDS parallel to utilization factor.