Resource Allocation with Exponential Model Prediction for Server Virtualization
Dulyawit Prangchumpol, Peraphon Sophatsathit, ChidchanokLursinsap, PanjaiTantasanawong
Journal of Digital Information Management, Vol. 13, No. 5, 2015.
DOI: 
Link: http://dline.info/fpaper/jdim/v13i5/v13i5_11.pdf
Abstract:
This paper proposes a practical and effective
predicting model for resource allocation and usage for
server. The approach rests on virtualization technique to
simulate a heterogeneous virtual machine environment.
The study is confined to management of number of CPUs
and memory units being allocated on three servers to
serve user's requests. The objective is fast response time
to attain as high user satisfaction as possible. The
algorithm employs exponential smoothing technique to
analyze trend of data and the relationship among them.
Assessment was compared with association rules and
ARIMA. The findings reveal that the proposed technique
yields more accurate prediction results than other
predicting models, having the least MSE and acceptable
system response time.