A fault-tolerant failure adaptively detection scheme in cloud networks

Most existing Failure Detector (FD) schemes do not automatically adjust their detection service parameters for the dynamic network conditions, thus they couldn´t be used for actual application. Firstly, this paper explores FD properties with relation to the actual and automatic fault-tolerant cloud computing networks, and proposes a general self-tuning failure detection method in the fault-tolerant cloud computing networks, and then based on the above general method, we propose an automatic Self-tuning Failure Detector (SFD) to optimize the existing FDs and explore the implementation of SFD. Finally, we comparatively evaluate our failure detection scheme and existing schemes by extensive experiments in seven representative Wide Area Network (WAN) cases. The experimental results show the properties of the different FDs, and demonstrate that our scheme can automatically adjust SFD control parameters to obtain corresponding services and satisfy user requirements, while maintaining good performance. Such an SFD can be extensively applied to industrial and commercial usage, and it can also significantly benefit the cloud networks.