Cloud storage systems are increasingly adopting NoSQL database management systems (DBMS), since they generally provide superior availability and performance than traditional DBMSs. To the detriment of better consistency guarantees, several NoSQL DBMSs allow eventual consistency, in which an operation is confirmed without checking all nodes. Different consistency levels for an operation (e.g. read) can be adopted, and such levels may distinctly affect system behaviour. Thus, the assessment of a system design taking into account distinct consistency levels is important for developing cloud storage systems. This work proposes an approach based on reliability block diagrams and generalized stochastic Petri nets to evaluate availability and performance of cloud storage systems, considering redundant nodes and eventual consistency based on NoSQL DBMS. Experimental results demonstrate system configuration may influence unavailability from 1 s to 21 h in a year, and performance can be impacted by up to 17.9%.

云存储系统越来越多地采用 NoSQL 数据库管理系统 (DBMS)，因为它们通常提供比传统 DBMS 更高的可用性和性能。为了不利于更好的一致性保证，一些 NoSQL DBMS 允许最终一致性，即在不检查所有节点的情况下确认操作。可以为操作（例如读取）采用不同的一致性级别，这些级别可能会明显影响系统行为。因此，考虑不同一致性级别的系统设计评估对于开发云存储系统很重要。这项工作提出了一种基于可靠性框图和广义随机 Petri 网的方法来评估云存储系统的可用性和性能，并基于 NoSQL DBMS 考虑冗余节点和最终一致性。