Distributed systems: concepts and design
Distributed systems: concepts and design
Towards robust distributed systems (abstract)
Proceedings of the nineteenth annual ACM symposium on Principles of distributed computing
Application specific data replication for edge services
WWW '03 Proceedings of the 12th international conference on World Wide Web
Distributed caching with memcached
Linux Journal
ACM Computing Surveys (CSUR)
Distributed Systems: Principles and Paradigms (2nd Edition)
Distributed Systems: Principles and Paradigms (2nd Edition)
Design and evaluation of a continuous consistency model for replicated services
OSDI'00 Proceedings of the 4th conference on Symposium on Operating System Design & Implementation - Volume 4
Bigtable: a distributed storage system for structured data
OSDI '06 Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation - Volume 7
Dynamo: amazon's highly available key-value store
Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles
Adaptive Consistency Guarantees for Large-Scale Replicated Services
NAS '08 Proceedings of the 2008 International Conference on Networking, Architecture, and Storage
PNUTS: Yahoo!'s hosted data serving platform
Proceedings of the VLDB Endowment
Cassandra: structured storage system on a P2P network
Proceedings of the 28th ACM symposium on Principles of distributed computing
Consistency rationing in the cloud: pay only when it matters
Proceedings of the VLDB Endowment
Benchmarking cloud serving systems with YCSB
Proceedings of the 1st ACM symposium on Cloud computing
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Today we are increasingly more dependent on critical data stored in cloud data centers across the world. To deliver high-availability and augmented performance, different replication schemes are used to maintain consistency among replicas. With classical consistency models, performance is necessarily degraded, and thus most highly-scalable cloud data centers sacrifice to some extent consistency in exchange of lower latencies to end-users. More so, those cloud systems blindly allow stale data to exist for some constant period of time and disregard the semantics and importance data might have, which undoubtedly can be used to gear consistency more wisely, combining stronger and weaker levels of consistency. To tackle this inherent and well-studied trade-off between availability and consistency, we propose the use of VFC3, a novel consistency model for replicated data across data centers with framework and library support to enforce increasing degrees of consistency for different types of data (based on their semantics). It targets cloud tabular data stores, offering rationalization of resources (especially bandwidth) and improvement of QoS (performance, latency and availability), by providing strong consistency where it matters most and relaxing on less critical classes or items of data.