Exploring Energy-Consistency Trade-Offs in Cassandra Cloud Storage System

Apache Cassandra is an open-source cloud storage system that offers multiple types of operation-level consistency including eventual consistency with multiple levels of guarantees and strong consistency. It is being used by many data-center applications (e.g., Facebook and App Scale). Most existing research efforts have been dedicated to exploring trade-offs such as: consistency vs. Performance, consistency vs. Latency and consistency vs. Monetary cost. In contrast, a little work is focusing on the consistency vs. Energy trade-off. As power bills have become a substantial part of the monetary cost for operating a data-center, this paper aims to provide a clearer understanding of the interplay between consistency and energy consumption. Accordingly, a series of experiments have been conducted to explore the implication of different factors on the energy consumption in Cassandra. Our experiments have revealed a noticeable variation in the energy consumption depending on the consistency level. Furthermore, for a given consistency level, the energy consumption of Cassandra varies with the access pattern and the load exhibited by the application. This further analysis indicates that the uneven distribution of the load amongst different nodes also impacts the energy consumption in Cassandra. Finally, we experimentally compare the impact of four storage configuration and data partitioning policies on the energy consumption in Cassandra: interestingly, we achieve 23% energy saving when assigning 50% of the nodes to the hot pool for the applications with moderate ratio of reads and writes, while applying eventual (quorum) consistency. This study points to opportunities for future research on consistency-energy trade-offs and offers useful insight into designing energy-efficient techniques for cloud storage systems.