Adaptive fault detection method for reliable cloud computing
Xia Min-n · Jisuanji yingyong yanjiu · 2014
This paper proposed an adaptive fault detection method to protect the reliability of cloud system. Firstly,it exacted the cloud metric using the incremental metric search algorithm and the metric space separation technology,which could obtain the best metric for characterizing the cloud behavior and the health status such as the maximal relevance criterion and the minimal redundancy criterion. And then mapped the data point of cloud metric into the kernel space to reduce the dimensionality by using the minimum enclosing sphere formulation. Finally,input the low-dimensional data into the fault detector,which generated a smallest enclose spherical with accommodating data in the kernel space to identify the potential failure. If the fault history could not be obtained,the fault detector would find the other states different from the cloud health status to identify the failure. The cloud operators verified and confirmed the detection results as either true failures or normal states( false alarms). It have implemented a prototype of the fault detection system and conducted experiments in an on-campus cloud computing environment. The experimental results show that the method can achieve more efficient and accurate failure detection than other existing schemes.