8,836 research outputs found

    Adaptive Consistency Guarantees for Large-Scale Replicated Services

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    To maintain consistency, designers of replicated services have traditionally been forced to choose from either strong consistency guarantees or none at all. Realizing that a continuum between strong and optimistic consistencies is semantically meaningful for a broad range of network services, previous research has proposed a continuous consistency model for replicated services to support the tradeoff between the guaranteed consistency level, performance and availability. However, to meet changing application needs and to make the model useful for interactive users of large-scale replicated services, the adaptability and the swiftness of inconsistency resolution are important and challenging. This paper presents IDEA (an Infrastructure for DEtection-based Adaptive consistency guarantees) for adaptive consistency guarantees of large-scale, Internet-based replicated services. The main functions enabled by IDEA include quick inconsistency detection and resolution, consistency adaptation and quantified consistency level guarantees. Through experimentation on the Planet-Lab, IDEA is evaluated from two aspects: its adaptive consistency guarantees and its performance for inconsistency resolution. Results show that IDEA is able to provide consistency guarantees adaptive to user’s changing needs, and it achieves low delay for inconsistency resolution and incurs small communication overhead

    Khazana: a flexible wide area data store

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    technical reportKhazana is a peer-to-peer data service that supports efficient sharing and aggressive caching of mutable data across the wide area while giving clients significant control over replica divergence. Previous work on wide-area replicated services focussed on at most two of the following three properties: aggressive replication, customizable consistency, and generality. In contrast, Khazana provides scalable support for large numbers of replicas while giving applications considerable flexibility in trading off consistency for availability and performance. Its flexibility enables applications to effectively exploit inherent data locality while meeting consistency needs. Khazana exports a file system-like interface with a small set of consistency controls which can be combined to yield a broad spectrum of consistency flavors ranging from strong consistency to best-effort eventual consistency. Khazana servers form failure-resilient dynamic replica hierarchies to manage replicas across variable quality network links. In this report, we outline Khazana?s design and show how its flexibility enables three diverse network services built on top of it to meet their individual consistency and performance needs: (i) a wide-area replicated file system that supports serializable writes as well as traditional file sharing across wide area, (ii) an enterprise data service that exploits locality by caching enterprise data closer to end-users while ensuring strong consistency for data integrity, and (iii) a replicated database that reaps order of magnitude gains in throughput by relaxing consistency

    Cache Serializability: Reducing Inconsistency in Edge Transactions

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    Read-only caches are widely used in cloud infrastructures to reduce access latency and load on backend databases. Operators view coherent caches as impractical at genuinely large scale and many client-facing caches are updated in an asynchronous manner with best-effort pipelines. Existing solutions that support cache consistency are inapplicable to this scenario since they require a round trip to the database on every cache transaction. Existing incoherent cache technologies are oblivious to transactional data access, even if the backend database supports transactions. We propose T-Cache, a novel caching policy for read-only transactions in which inconsistency is tolerable (won't cause safety violations) but undesirable (has a cost). T-Cache improves cache consistency despite asynchronous and unreliable communication between the cache and the database. We define cache-serializability, a variant of serializability that is suitable for incoherent caches, and prove that with unbounded resources T-Cache implements this new specification. With limited resources, T-Cache allows the system manager to choose a trade-off between performance and consistency. Our evaluation shows that T-Cache detects many inconsistencies with only nominal overhead. We use synthetic workloads to demonstrate the efficacy of T-Cache when data accesses are clustered and its adaptive reaction to workload changes. With workloads based on the real-world topologies, T-Cache detects 43-70% of the inconsistencies and increases the rate of consistent transactions by 33-58%.Comment: Ittay Eyal, Ken Birman, Robbert van Renesse, "Cache Serializability: Reducing Inconsistency in Edge Transactions," Distributed Computing Systems (ICDCS), IEEE 35th International Conference on, June~29 2015--July~2 201
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