Hybrid Genetic Algorithms for Scheduling High-Speed Multimedia Systems

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Hybrid Genetic Algorithms for Scheduling High-Speed Multimedia Systems

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Abstract

It has been observed that most conventional operating systems could not cope with the scheduling of multimedia tasks owing to the large size of these files. For instance, processing of multimedia tasks using the traditional operating systems are fraught with problems such as low quality of service and delay jitters. In order to address these problems, a scheduling algorithm christened hybrid genetic algorithm for multimedia task scheduling (HGAMTS) was developed. It employed heuristic knowledge of the problem domain to model a hybrid genetic algorithm in a multiprocessor environment. The system is made up of the scheduler model and the task model. The scheduler model consist a centralized dynamic scheduling scheme. In this scheme, all tasks arrive at a central processor (scheduler). The model has a minimum of five and maximum of ten processors. Attached to each processor is a dispatch queue.

References

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Oluwadare Samuel Adebayo, Olabode Olatunbosun, Iwasokun Gabriel Babatunde. 2015. "Hybrid Genetic Algorithms for Scheduling High-Speed Multimedia Systems". Global Journal of Computer Science and Technology - B: Cloud & Distributed GJCST-B Volume 15 (GJCST Volume 15 Issue B4).

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords
Classification
GJCST-B Classification B.2.4
Version of record

v1.2

Issue date
October 5, 2015

Language
English
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Hybrid Genetic Algorithms for Scheduling High-Speed Multimedia Systems

Oluwadare Adebayo
Oluwadare Adebayo The Federal University of Technology, Akure, Nigeria
Olabode Olatunbosun
Olabode Olatunbosun
Iwasokun Babatunde
Iwasokun Babatunde