Astrom K. J.

Kai-Yuan Cai

Ke-Xian Xue

Killelea P.

Kumar S.

Lei Zhao

Yun-Fei Jia

Zhi Quan Zhou

 Software aging refers to the phenomenon that software systems show progressive performance degradation or a sudden crash after longtime execution. It has been reported that this phenomenon is closely related to the exhaustion of system resources. This paper quantitatively studies available system resources under the real-world situation where workload changes dynamically over time. We propose a neural network approach to first investigate the relationship between available system resources and system workload and then to forecast future available system resources. Experimental results on data sets collected from real-world computer systems demonstrate that the proposed approach is effective. </jats:p

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International Journal of Software Engineering and Knowledge Engineering

Using Neural Networks to Forecast Available System Resources: An Approach and Empirical Investigation

http://ro.uow.edu.au/cgi/viewcontent.cgi?article=6238&context=eispapers

Using Neural Networks to Forecast Available System Resources: An Approach and Empirical Investigation

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