Hybrid Genetic Algorithms for Scheduling High-Speed Multimedia Systems

1
Oluwadare Samuel Adebayo
Oluwadare Samuel Adebayo
2
Olabode Olatunbosun
Olabode Olatunbosun
3
Iwasokun Gabriel Babatunde
Iwasokun Gabriel Babatunde
4
Akinyede Raphael Olufemi
Akinyede Raphael Olufemi
1 The Federal University of Technology, Akure, Nigeria

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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.

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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.

Oluwadare Samuel Adebayo. 2015. \u201cHybrid Genetic Algorithms for Scheduling High-Speed Multimedia Systems\u201d. Global Journal of Computer Science and Technology - B: Cloud & Distributed GJCST-B Volume 15 (GJCST Volume 15 Issue B4): .

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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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GJCST-B Classification: B.2.4
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v1.2

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October 5, 2015

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English

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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.

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Hybrid Genetic Algorithms for Scheduling High-Speed Multimedia Systems

Oluwadare Samuel Adebayo
Oluwadare Samuel Adebayo The Federal University of Technology, Akure, Nigeria
Olabode Olatunbosun
Olabode Olatunbosun
Iwasokun Gabriel Babatunde
Iwasokun Gabriel Babatunde
Akinyede Raphael Olufemi
Akinyede Raphael Olufemi

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