An algorithm for concurrency control and recovery in replicated distributed databases
ACM Transactions on Database Systems (TODS)
Serializability theory for replicated databases
Journal of Computer and System Sciences
The dangers of replication and a solution
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Towards robust distributed systems (abstract)
Proceedings of the nineteenth annual ACM symposium on Principles of distributed computing
Don't Be Lazy, Be Consistent: Postgres-R, A New Way to Implement Database Replication
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Load prediction models in web-based systems
valuetools '06 Proceedings of the 1st international conference on Performance evaluation methodolgies and tools
Bigtable: a distributed storage system for structured data
OSDI '06 Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation - Volume 7
Serializable isolation for snapshot databases
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
PNUTS: Yahoo!'s hosted data serving platform
Proceedings of the VLDB Endowment
Consistency rationing in the cloud: pay only when it matters
Proceedings of the VLDB Endowment
Revising 1-Copy Equivalence in Replicated Databases with Snapshot Isolation
OTM '09 Proceedings of the Confederated International Conferences, CoopIS, DOA, IS, and ODBASE 2009 on On the Move to Meaningful Internet Systems: Part I
Flexible Data Access in a Cloud Based on Freshness Requirements
CLOUD '10 Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing
Cost-Based Data Consistency in a Data-as-a-Service Cloud Environment
CLOUD '12 Proceedings of the 2012 IEEE Fifth International Conference on Cloud Computing
Spanner: Google's globally-distributed database
OSDI'12 Proceedings of the 10th USENIX conference on Operating Systems Design and Implementation
Event aware workload prediction: a study using auction events
WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
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Clouds are very attractive environments for deploying different types of applications due to their pay-as-you-go cost model and their highly available and scalable infrastructure. Data management is an integral part of the applications deployed in the Cloud. Thus, it is of outmost importance to provide highly available and scalable data management solutions tailored to the needs of the Cloud. Data availability can be increased by using well-known replication techniques. Data replication also increases scalability in case of read-only transactions, but generates a considerable overhead for keeping the replicas consistent in case of update transactions. In order to meet the scalability demands of their customers, current Cloud providers use DBMSs that only support weak data consistency. While weak consistency is considered to be sufficient for many of the currently deployed applications in the Cloud, more and more applications with strong consistency guarantees, like traditional online stores, are moved to the Cloud. In the presence of replicated data, these applications require one-copy serializability (1SR). Hence, in order to exploit the advantages of the Cloud also for these applications, it is essential to provide scalable, available, low-cost, and strongly consistent data management, which is able to adapt dynamically based on application and system conditions. In this paper, we present SO-1SR (self-optimizing 1SR), a novel customizable load balancing approach to transaction execution on top of replicated data in the Cloud which is able to efficiently use existing resources and to optimize transaction execution in an adaptive and dynamic manner without a dedicated load balancing component. The evaluation of SO-1SR on the basis of the TPC-C benchmark in the AWS Cloud environment has shown that the SO-1SR load balancer is much more efficient compared to existing load balancing techniques.