On scalable and efficient distributed failure detectors
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We study the quality of service (QoS) of failure detectors. By QoS, we mean a specification that quantifies (a) how fast the failure detector detects actual failures, and (b) how well it avoids false detections. We first propose a set of QoS metrics to specify failure detectors for systems with probabilistic behaviors, i.e., for systems where message delays and message losses follow some probability distributions. We then give a new failure detector algorithm and analyze its QoS in terms of the proposed metrics. We show that, among a large class of failure detectors, the new algorithm is optimal with respect to some of these QoS metrics. Given a set of failure detector QoS requirements, we show how to compute the parameters of our algorithm so that it satisfies these requirements, and we show how this can be done even if the probabilistic behavior of the system is not known. Finally, we briefly explain how to make our failure detector adaptive, so that it automatically reconfigures itself when there is a change in the probabilistic behavior of the network.