The Design and Implementation of Job Management System Based on Feedback Control

Author

Cao, HaiBin ; Lu, BaoFeng ; Zhu, Ming

Author_Institution

Dept. of Autom., Univ. of Sci. & Technol. of China, Hefei, China

fYear

2010

fDate

10-12 Aug. 2010

Firstpage

198

Lastpage

201

Abstract

We design and implement a Job Management System for improving automation level of job execution process in network-based digital multimedia content production. Jobs are automatically parallelized and executed on a large number of execution machines. Our implementation of the Job Management System has two novel aspects. One aspect is using a feedback mechanism in execution time estimation base on Extreme Learning Machine (ELM) for self-optimizing. Based on the feedback mechanism, we can continually use the newly obtained data to improve the system. The other one is having the capability of autonomic fault recovery. The system has been integrated to a network-based digital multimedia content production platform.

Keywords

content management; distributed processing; feedback; multimedia computing; automation level; execution machine; execution time estimation; extreme learning machine; feedback control; job execution process; job management system; network-based digital multimedia content production; Benchmark testing; Estimation; Multimedia communication; Neurons; Scheduling; ELM; Job Management; distributed computing; feedback control;

fLanguage

English

Publisher

ieee

Conference_Titel

Distributed Computing and Applications to Business Engineering and Science (DCABES), 2010 Ninth International Symposium on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-7539-1

Type

conf

DOI

10.1109/DCABES.2010.46

Filename

5572081