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Journal of Engineering
Volume 2014, Article ID 485361, 13 pages
http://dx.doi.org/10.1155/2014/485361
Research Article

Performance Evaluation of New Joint EDF-RM Scheduling Algorithm for Real Time Distributed System

Department of Computer Science & Engineering and Information & Communication Technology, Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh 173234, India

Received 27 May 2013; Accepted 25 November 2013; Published 22 January 2014

Academic Editor: WaiKeung Wong

Copyright © 2014 Rashmi Sharma and Nitin. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In Real Time System, the achievement of deadline is the main target of every scheduling algorithm. Earliest Deadline First (EDF), Rate Monotonic (RM), and least Laxity First are some renowned algorithms that work well in their own context. As we know, there is a very common problem Domino's effect in EDF that is generated due to overloading condition (EDF is not working well in overloading situation). Similarly, performance of RM is degraded in underloading condition. We can say that both algorithms are complements of each other. Deadline missing in both events happens because of their utilization bounding strategy. Therefore, in this paper we are proposing a new scheduling algorithm that carries through the drawback of both existing algorithms. Joint EDF-RM scheduling algorithm is implemented in global scheduler that permits task migration mechanism in between processors in the system. In order to check the improved behavior of proposed algorithm we perform simulation. Results are achieved and evaluated in terms of Success Ratio (SR), Average CPU Utilization (ECU), Failure Ratio (FR), and Maximum Tardiness parameters. In the end, the results are compared with the existing (EDF, RM, and D_R_EDF) algorithms. It has been shown that the proposed algorithm performs better during overloading condition as well in underloading condition.