Hybrid Genetic Algorithms for Scheduling High-Speed Multimedia Systems

Article ID

CSTB763P8

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
DOI

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.

Hybrid Genetic Algorithms for Scheduling High-Speed Multimedia Systems

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.

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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Oluwadare Samuel Adebayo. 2015. “. 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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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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