A dynamic load balancing strategy for cloud computing platform based on exponential smoothing forecast

Author

Ren, Xiaona ; Lin, Rongheng ; Zou, Hua

Author_Institution

State Key Lab. of Networking & Switching Techonlogy, Beijing Univ. of Posts & Telecommun., Beijing, China

fYear

2011

fDate

15-17 Sept. 2011

Firstpage

220

Lastpage

224

Abstract

Because of the elastic service capability of cloud computing platform, more and more applications are moved here, which makes efficient load balancing into a bottleneck. Considering the unique features of long-connectivity applications which are increasingly popular nowadays, an improved algorithm is proposed based on the weighted least connection algorithm. In the new algorithm, load and processing power are quantified, and single exponential smoothing forecasting mechanism is added. Finally, the article proves by experiments that the new algorithm can reduce the server load tilt, and improve client service quality effectively.

Keywords

cloud computing; resource allocation; client service quality improvement; cloud computing platform; dynamic load balancing strategy; elastic service capability; long-connectivity applications; server load tilt reduction; single exponential smoothing forecasting mechanism; weighted least connection algorithm; Algorithm design and analysis; Forecasting; Heuristic algorithms; Load management; Servers; Smoothing methods; Training; cloud computing; exponential smoothing forecast; load balancing; long connection;

fLanguage

English

Publisher

ieee

Conference_Titel

Cloud Computing and Intelligence Systems (CCIS), 2011 IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-61284-203-5

Type

conf

DOI

10.1109/CCIS.2011.6045063

Filename

6045063