New Fuzzy Scheduling Algorithm (Nfsa) for Real- Time Tasks on Multiprocessor Systems

Description

Download New Fuzzy Scheduling Algorithm (Nfsa) for Real- Time Tasks on Multiprocessor Systems. Mathematics students who are writing their projects can get this material to aid their research work.

Abstract

This thesis is an extension of existing fuzzy scheduling algorithms, to schedule real-time tasks on multiprocessor systems.

The existing fuzzy scheduling algorithm was extended in order to have a better performance at higher system load. The task scheduling parameters used in this research work are; arrival time, computation time, and deadline which are inputs to the fuzzy inference system.

The outputs are the runtime priorities which are used to schedule tasks in a priority (ready) queue for execution on multiprocessor. The performance of the new fuzzy scheduling algorithm was compared with the existing fuzzy scheduling algorithm.

Results show that the new fuzzy algorithm has a better performance than the existing algorithm at higher system load; this is as a result of minimum response time, turnaround time and lower number of tasks that missed their deadline.

Introduction

Scheduling algorithm is more significant in a real-time system to ensure desired and predictable behaviour of a system (Sagar et al., 2012).

Scheduling is concern with the optimal allocation of resources to tasks in a specified time. Real-time systems are often embedded in most of domestic devices which are used for daily activities without our knowledge when we use the devices in which they reside.

Cars, planes and entertainment systems are just some devices in which real-time systems reside, governing the workings of that device while we do not consider that such a system exists within the chosen device.

A real-time-system is a computer system in which the key aspect of the system is to perform tasks on time, not finishing too early nor too late. A classic example is that of the air-bag in a car; it is of great importance that the bag inflates neither too soon nor too late in orders to be of help and not be potentially harmful.

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