Title :
Study on timely scheduling algorithm for load balance based on Support Vector Machine
Author :
Shi Qiaoshuo ; Li Chongchong ; Li Jungang
Author_Institution :
School of Computer Science and Software Engineering, Hebei University of Technology, Tianjin, China
Abstract :
A timely scheduling model is studied and a solution on load balance is attempted to explore from the point of machine learning in this paper. An expert system scheduling algorithm based on Support Vector Machine is presented. After research, the corresponding scheduling model is built, which is applied to the load balance of server cluster. Finally, the feasibility and validity of the algorithm is validated through experiments.
Keywords :
Accuracy; Nickel; Presses; Random access memory; Servers; Training; Support Vector Machine; load balance; machine learning; scheduling; server cluster;
Conference_Titel :
Conference Anthology, IEEE
Conference_Location :
China
DOI :
10.1109/ANTHOLOGY.2013.6784996