Comparative Analysis of QoS and Memory Usage of Adaptive Failure Detectors

This paper compares several parametric and adaptive failure detection schemes in terms of their respective QoS. We introduce an improvement over existing methods, and evaluate their benefits. First, we propose an optimization to enhance the adaptation of Chen´s FD, which significantly improves QoS, especially in the aggressive range and when the network is unstable. Second, we address the problem of most adaptive schemes, namely their need for a large window of samples. We study a scheme that is designed to use a fixed and very limited amount of memory for each monitored-monitoring link. Our experimental results over several kinds of networks (Cluster, WiFi, wired LAN, WAN) show that the properties of the existing adaptive FDs, and that the optimization is reasonable and acceptable. Furthermore, the extensive experimental results show what is the effect of memory size on the overall QoS of each adaptive FD.