Research Article
A Heuristic Model for Tasks Scheduling in Heterogeneous Distributed Real Time System under Fuzzy Environment
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 111 - Issue 2 |
| Published: February 2015 |
| Authors: Harendra Kumar |
10.5120/19512-1131
|
Harendra Kumar . A Heuristic Model for Tasks Scheduling in Heterogeneous Distributed Real Time System under Fuzzy Environment. International Journal of Computer Applications. 111, 2 (February 2015), 35-43. DOI=10.5120/19512-1131
@article{ 10.5120/19512-1131,
author = { Harendra Kumar },
title = { A Heuristic Model for Tasks Scheduling in Heterogeneous Distributed Real Time System under Fuzzy Environment },
journal = { International Journal of Computer Applications },
year = { 2015 },
volume = { 111 },
number = { 2 },
pages = { 35-43 },
doi = { 10.5120/19512-1131 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2015
%A Harendra Kumar
%T A Heuristic Model for Tasks Scheduling in Heterogeneous Distributed Real Time System under Fuzzy Environment%T
%J International Journal of Computer Applications
%V 111
%N 2
%P 35-43
%R 10.5120/19512-1131
%I Foundation of Computer Science (FCS), NY, USA
Abstract
The development of distributed real time system (DRTS) has lead to there use in several applications including information processing, fluid flow, weather modeling, database systems, real-time high-speed simulation of dynamical systems, and image processing. Reliability analysis of these processing elements and communication links is one of the important parameter to get the system efficiency. We can improve the system performance (i. e. system cost, system reliability and processor utilization etc. ) by scheduling the tasks to the processors properly in DRTS. In this paper, a new tasks allocation model has been developed with fuzzy execution times e ?_(i,j) and fuzzy inter tasks communication times c ?_(i,j). The times has been defuzzified into crisp one by using Robust Ranking Method [RRM], Centre of Maxima Method [CoM] and Weight of Center of Area Method [CoA]. The effect of inter processor distances on the tasks allocation has been considered while developing the model. Numerical examples show that the model presented in this paper is suitable for arbitrary number of processors with random program structure and more realistic and general in nature.
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