An algorithm for concurrency control and recovery in replicated distributed databases
ACM Transactions on Database Systems (TODS)
Coda: A Highly Available File System for a Distributed Workstation Environment
IEEE Transactions on Computers
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
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OceanStore: an architecture for global-scale persistent storage
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PDIS '94 Proceedings of the third international conference on on Parallel and distributed information systems
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Bayou: replicated database services for world-wide applications
EW 7 Proceedings of the 7th workshop on ACM SIGOPS European workshop: Systems support for worldwide applications
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IEEE/ACM Transactions on Networking (TON)
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ACM SIGOPS Operating Systems Review - OSDI '02: Proceedings of the 5th symposium on Operating systems design and implementation
The impact of DHT routing geometry on resilience and proximity
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
The Ficus Replicated File System
ACM SIGOPS Operating Systems Review
Failure trends in a large disk drive population
FAST '07 Proceedings of the 5th USENIX conference on File and Storage Technologies
Dynamo: amazon's highly available key-value store
Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles
A self-organized, fault-tolerant and scalable replication scheme for cloud storage
Proceedings of the 1st ACM symposium on Cloud computing
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Hardware failures in current data centers are common partly due to the higher data scales supported. Data replication is the common approach for improving availability. However, mostly static replication approaches have been proposed, i.e. the number of replicas and their locations are fixed. Moreover, the geographical diversity of data locations has not explicitly been considered. In this paper, we propose a cost-efficient replication scheme across data centers that dynamically adapts the number of replicas employed per partition to the query load, while maintaining availability guarantees in case of failures. Our approach employs a virtual economy that is experimentally proved in a simulated environment to achieve load balancing among data servers at the minimum cost.