Extending Eventually Consistent Cloud Databases for Enforcing Numeric Invariants

Geo-replicated databases often operate under the principle of eventual consistency to offer high-availability with low latency on a simple key/value store abstraction. Recently, some have adopted commutative data types to provide seamless reconciliation for special purpose data types, such as counters. Despite this, the inability to enforce numeric invariants across all replicas still remains a key shortcoming of relying on the limited guarantees of eventual consistency storage. We present a new replicated data type, called bounded counter, which adds support for numeric invariants to eventually consistent geo-replicated databases. We describe how this can be implemented on top of existing cloud stores without modifying them, using Riak as an example. Our approach adapts ideas from escrow transactions to devise a solution that is decentralized, fault-tolerant and fast. Our evaluation shows much lower latency and better scalability than the traditional approach of using strong consistency to enforce numeric invariants, thus alleviating the tension between consistency and availability

Asynchronous replication of eventually consistent updatable views

Users of software applications expect fast response times and high availability. This is despite several applications moving from local devices and into the cloud. A cloud-based application that could function locally will now be unavailable if a network partition occurs. A fundamental challenge in distributed systems is maintaining the right tradeoffs between strong consistency, high availability, and tolerance to network partitions. The impossibility of achieving all three properties is described in the CAP theorem. To guarantee the highest degree of responsiveness and availability, applications could be run entirely locally on a device without directly relying on cloud services. Software that can be run locally without a direct dependency on cloud services are called local-first software. Being local-first means that consistency guarantees may need to be relaxed. Weaker consistency, such as eventual consistency, can be used instead of strong consistency. Implementing conflict-free replicated data types (CRDTs) is a provably correct way to achieve eventual consistency. These data types guarantee that the state of different replicas will converge towards a common state when a system becomes connected and quiescent. The drawback of using CRDTs is that they are unbounded in their growth. This means they can quickly become too large to handle using less capable devices like smartphones, tablets, or other edge devices. To mitigate this, partial replication can be implemented to replicate only the data each device needs. This comes with the added benefit of limiting the information users obtain, thus possibly improving security and privacy. The main contribution of this thesis is a new approach to partial replication. It is based on an existing asynchronously replicated relational database to support local-first software and guarantees eventual consistency. The new approach uses database views to define partial replicas. The database views are made updatable by drawing inspiration from the large body of research on updatable views. We differentiate ourselves from earlier work on non-distributed updatable views by guaranteeing that the views are eventually consistent. The approach is evaluated to ensure it can be used for real scenarios. The approach has proved to be usable in the scenarios. The replication of database views has also been experimentally tested to ensure that our approach to partial replication is viable for less capable devices

On the Behaviour of General-Purpose Applications on Cloud Storages

Managing data over cloud infrastructures raises novel challenges with respect to existing and well studied approaches such as ACID and long running transactions. One of the main requirements is to provide availability and partition tolerance in a scenario with replicas and distributed control. This comes at the price of a weaker consistency, usually called eventual consistency. These weak memory models have proved to be suitable in a number of scenarios, such as the analysis of large data with Map-Reduce. However, due to the widespread availability of cloud infrastructures, weak storages are used not only by specialised applications but also by general purpose applications. We provide a formal approach, based on process calculi, to reason about the behaviour of programs that rely on cloud stores. For instance, one can check that the composition of a process with a cloud store ensures `strong' properties through a wise usage of asynchronous message-passing

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

International audienceApache 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 AppScale). 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

Archiving the Relaxed Consistency Web

The historical, cultural, and intellectual importance of archiving the web has been widely recognized. Today, all countries with high Internet penetration rate have established high-profile archiving initiatives to crawl and archive the fast-disappearing web content for long-term use. As web technologies evolve, established web archiving techniques face challenges. This paper focuses on the potential impact of the relaxed consistency web design on crawler driven web archiving. Relaxed consistent websites may disseminate, albeit ephemerally, inaccurate and even contradictory information. If captured and preserved in the web archives as historical records, such information will degrade the overall archival quality. To assess the extent of such quality degradation, we build a simplified feed-following application and simulate its operation with synthetic workloads. The results indicate that a non-trivial portion of a relaxed consistency web archive may contain observable inconsistency, and the inconsistency window may extend significantly longer than that observed at the data store. We discuss the nature of such quality degradation and propose a few possible remedies.Comment: 10 pages, 6 figures, CIKM 201

An optimized conflict-free replicated set

Eventual consistency of replicated data supports concurrent updates, reduces latency and improves fault tolerance, but forgoes strong consistency. Accordingly, several cloud computing platforms implement eventually-consistent data types. The set is a widespread and useful abstraction, and many replicated set designs have been proposed. We present a reasoning abstraction, permutation equivalence, that systematizes the characterization of the expected concurrency semantics of concurrent types. Under this framework we present one of the existing conflict-free replicated data types, Observed-Remove Set. Furthermore, in order to decrease the size of meta-data, we propose a new optimization to avoid tombstones. This approach that can be transposed to other data types, such as maps, graphs or sequences.Comment: No. RR-8083 (2012