Geo-replicated storage systems are at the core of current Internet services. The designers of the replication protocols used by these systems must choose between either supporting low-latency, eventually-consistent operations, or ensuring strong consistency to ease application correctness. We propose an alternative consistency model, Explicit Consistency, that strengthens eventual consistency with a guarantee to preserve specific invariants defined by the applications. Given these application-specific invariants, a system that supports Explicit Consistency identifies which operations would be unsafe under concurrent execution, and allows programmers to select either violation-avoidance or invariant-repair techniques. We show how to achieve the former, while allowing operations to complete locally in the common case, by relying on a reservation system that moves coordination off the critical path of operation execution. The latter, in turn, allows operations to execute without restriction, and restore invariants by applying a repair operation to the database state. We present the design and evaluation of Indigo, a middleware that provides Explicit Consistency on top of a causally-consistent data store. Indigo guarantees strong application invariants while providing similar latency to an eventually-consistent system in the common case.

This paper studies the semantics of sets under eventual consistency. The set is a pervasive data type, used either directly or as a component of more complex data types, such as maps or graphs. Eventual consistency of replicated data supports concurrent updates, reduces latency and improves fault tolerance, but forgoes strong consistency (e.g., linearisability). Accordingly, several cloud computing platforms implement eventually-consistent replicated sets [2,4].The sequential semantics of a set are well known, and are defined by individual updates, e.g., {true}add(e){e ∈ S} (in "{pre-condition} computation {post-condition}" notation), where S denotes its abstract state. However, the semantics of concurrent modifications is left underspecified or implementationdriven.We propose the following Principle of Permutation Equivalence to express that concurrent behaviour conforms to the sequential specification: "If all sequential permutations of updates lead to equivalent states, then it should also hold that concurrent executions of the updates lead to equivalent states." It implies the following behavior, for some updates u and u :Specifically for replicated sets, the Principle of Permutation Equivalence requires that {e = f }add(e) remove(f ){e ∈ S ∧ f / ∈ S}, and similarly for operations on different elements or idempotent operations. Only the pair add(e) remove(e) is unspecified by the principle, since add(e); remove(e) differs from remove(e); add(e). Any of the following post-conditions ensures a deterministic result:{⊥e ∈ S} -Error mark {e ∈ S} -add wins {e / ∈ S} -remove wins {add(e) > CLK remove(e) ⇔ e ∈ S} -Last Writer Wins (LWW) where < CLK compares unique clocks associated with the operations. Note that

Abstract-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.

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Abstract. It is common that, in a long-term asynchronous collaborative activity, groups of users engage in occasional synchronous sessions. In this paper, we analyze the requirements for supporting this common work practice in typical collaborative activities and applications. This analysis shows that, for some applications, it is necessary to rely on different data sharing techniques in synchronous and asynchronous settings. We present a data management system that allows to integrate a synchronous session in the context of a long-term asynchronous interaction, using the suitable data sharing techniques in each setting. We exemplify the use of our system with two multi-synchronous applications.