Comparison of Madame-Type and Sugeno-Type Fuzzy Inference Systems for Fuzzy Real Time Scheduling

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The classical analysis of real time systems tries to ensure that the instance of every task finishes before its absolute deadline (strict guarantee). The probabilistic approach tends to estimate the probability that it will happen. The deterministic timed behavior is an important parameter for analyzing the robustness of the system. Most of related works are mainly based on the determinism of time constraints. However, in most cases, these parameters are non precise. The vagueness of parameters suggests the use of fuzzy logic to decide in what order the requests should be executed to reduce the chance of a request being missed. The choice of task parameters and numbers of rules in fuzzy inference engine influences directly generated outputs. Fuzzy inference systems are developed for real time task using Mamdani-type and Sugeno-type fuzzy models. The results of the two fuzzy inference systems (FIS) are compared. This paper outlines the basic difference between the Mamdanitype FIS and Sugeno-type FIS. It also shows which one is a better choice of the two FIS for real time system.

Published In : IJCSN Journal Volume 5, Issue 5

Date of Publication : October 2016

Pages : 770-775

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Mohammed Blej : received his Master in analysis and computer science in 2004 from the Faculty of Sciences, Oujda, Morocco. Then he received his Ph.D in Computer Science in the same faculty in 2011. He is currently Professor at the CRMEF “ Centre Régional des Métiers de l’Enseignement et de Formation”, Oujda, Morocco. His teaching and research areas include real time system, testing real time system, Petri nets, Fuzzy Petri nets, Fuzzy scheduling, ITC, ITCE.

Mostafa Azizi : received his engineer diploma in Automatic and Industrial Computer Engineering in 1993 from the Mohammadia High School of Engineers (Rabat, Morocco). Then he received his Ph.D in Computer Science in 2001 from the University of Montreal (Montreal, Canada). He is currently Professor at the Mohamed 1st University (Oujda, Morocco). His main research interests include the aspects of real time in computer systems, embedded systems, systems security, inter-communication and management of computer systems in industrial environment.

Fuzzy Real Time Scheduling, Fuzzy Logic, Fuzzy Inference System (FIS), FIS Mamdani-Type

This paper described the two most commonly used Fuzzy inference systems to improve the priority of a task in a realtime system. It can be concluded from this paper that for fuzzy real time scheduling, Mamdani-type FIS and Sugeno-type FIS performs similarly but by using Sugenotype FIS model it allows the system to work at its full capacity. The choice of parameters and numbers of rules in fuzzy inference engine influences directly generated outputs. Being based on Mamdani or Sugeno, Fuzzy Inference Systems (FIS) are still on-going research areas. As a future work, as these results are based on simulation, we plan to study the problem theoretically to prove this result.

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