A quantitative analysis of quorum system availability in data centers

Large-scale distributed storage systems often replicate data across servers and even geographically-distributed data centers for high availability, while existing theories like CAP and PACELC show that there is a tradeoff between availability and consistency. However, current practice is mainly experience-based and lacks quantitative analysis for identifying a good tradeoff between the two. In this work, we are concerned with providing a quantitative analysis on availability for widely-used quorum systems in data centers. First, a probabilistic model is presented to quantify availability for typical data center networks: 2-tier basic tree, 3-tier basic tree, fat tree and folded clos network. Second, we build the availability-consistency table and propose a set of rules to quantitatively make tradeoff between availability and consistency. Finally, with Monte Carlo based simulations, we validate our presented quantitative results and show that our approach to make tradeoff between availability and consistency is effective.