An efficient adaptive failure detection mechanism for cloud platform based on volterra series

Failure detection module is one of important components in fault-tolerant distributed systems, especially cloud platform. However, to achieve fast and accurate detection of failure becomes more and more difficult especially when network and other resources´ status keep changing. This study presented an efficient adaptive failure detection mechanism based on volterra series, which can use a small amount of data for predicting. The mechanism uses a volterra filter for time series prediction and a decision tree for decision making. Major contributions are applying volterra filter in cloud failure prediction, and introducing a user factor for different QoS requirements in different modules and levels of IaaS. Detailed implementation is proposed, and an evaluation is performed in Beijing and Guangzhou experiment environment.