Abstract
One of the most important goals for companies that provide cloud computing services is to maintain high availability on large computer systems. In order to accomplish such objective, it is necessary to discovery the reason of poor availability. Software aging is a main factor in cloud computing services, leading to software failures, poor performances and may result in system downtime. This paper investigates the software aging effects on the OpenStack cloud computing platform and describes a forecasting model based on Hidden Markov Models. The prediction analysis of the Hidden Markov Models on the key performance data of the system shows that the Hidden Markov Models has excellent predictive performance and is suitable for the prediction of the reliability of the cloud server system.
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