NDLI: A new genetic-based algorithm for scheduling static tasks in homogeneous parallel systems

Content Provider	IEEE Xplore Digital Library
Author	Al Na'mneh, R.A. Darabkh, K.A.
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. Eng., Univ. of Jordan, Amman, Jordan (Darabkh, K.A.) \|\| Dept. of Software Eng., Jordan Univ. of Sci. & Technol., Irbid, Jordan (Al Na'mneh, R.A.)
Abstract	Task scheduling on multiprocessor systems is of a great interest since it is a computationally difficult problem due to having the possibility of failing in exploiting the true potential of the multiprocessor system as a result of inappropriate scheduling of available tasks. Static scheduling using genetic algorithms is a very popular approach as of being able to efficiently use the available machines and resources. In this paper, we propose an efficient algorithm, namely, sequence algorithm as a novel extension to a traditional existing generic algorithm to solve the task scheduling problem in multiprocessors systems through minimizing the tasks completion time and maximizing the throughput of the system. To achieve that, our proposed algorithm has its own way to initialize the chromosomes. Moreover, it uses a new systematic method for the crossover operator. In our work, we ignore the communication delay between tasks. To show the effectiveness of the proposed algorithm, we performed experimental simulations to see how far we need to go, for reproducing generations, to obtain acceptable efficiency. Actually, the results show that we can obtain a variance less than 10% (efficiency ≥ 90%) with a small number of iterations. By comparing the proposed algorithm with an existing genetic-based algorithm, it is found that the efficiency of the new algorithm to find a suboptimal schedule is increased for a fixed number of generations which in turn leads to decreasing the length of schedule or the completion time.
Sponsorship	IEEE Indonesia Sect. CS/RA Joint Chapt.
Starting Page	46
Ending Page	50
File Size	668379
Page Count	5
File Format	PDF
e-ISBN	9781479912087
DOI	10.1109/ROBIONETICS.2013.6743576
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-11-25
Publisher Place	Indonesia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Heuristic algorithms Sequence algorithm Static scheduling Genetics Robustness NP-complete Biological cells
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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