[tel-01086358] Ensuring consistency in partially replicated data stores

In the first part, we study consistency in a transactional systems, and focus on reconciling scalability with strong transactional guarantees. We identify four scalability properties, and show that none of the strong consistency criteria ensure all four. We define a new scalable consistency criterion called Non-Monotonic Snapshot Isolation (NMSI), while is the first that is compatible with all four properties. We also present a practical implementation of NMSI, called Jessy, which we compare experimentally against a number of well-known criteria. We also introduce a framework for performing fair comparison among different transactional protocols. Our insight is that a large family of distributed transactional protocols have a common structure, called Deferred Update Replication (DUR). Protocols of the DUR family differ only in behaviors of few generic functions. We present a generic DUR framework, called G-DUR. We implement and compare several transactional protocols using the G-DUR framework.In the second part, we focus on ensuring consistency in non-transactional data stores. We introduce Tuba, a replicated key-value store that dynamically selects replicas in order to maximize the utility delivered to read operations according to a desired consistency defined by the application. In addition, unlike current systems, it automatically reconfigures its set of replicas while respecting application-defined constraints so that it adapts to changes in clients’ locations or request rates. Compared with a system that is statically configured, our evaluation shows that Tuba increases the reads that return strongly consistent data by 63%.



from HAL : Dernières publications http://ift.tt/1xKN5n7