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Consistency in a partitioned network: a survey
ACM Computing Surveys (CSUR)
A quorum-consensus replication method for abstract data types
ACM Transactions on Computer Systems (TOCS)
Serializability theory for replicated databases
Journal of Computer and System Sciences
Concurrency control and recovery in database systems
Concurrency control and recovery in database systems
A measure of transaction processing power
Datamation
SIGMOD '87 Proceedings of the 1987 ACM SIGMOD international conference on Management of data
Maintaining availability in partitioned replicated databases
ACM Transactions on Database Systems (TODS)
Increasing availability under mutual exclusion constraints with dynamic vote reassignment
ACM Transactions on Computer Systems (TOCS)
Coda: A Highly Available File System for a Distributed Workstation Environment
IEEE Transactions on Computers
An efficient and fault-tolerant solution for distributed mutual exclusion
ACM Transactions on Computer Systems (TOCS)
ACM Transactions on Computer Systems (TOCS)
Experimental analysis of replication in distributed systems
Experimental analysis of replication in distributed systems
Cluster-based file replication in large-scale distributed systems
SIGMETRICS '92/PERFORMANCE '92 Proceedings of the 1992 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
A high availability N hierarchical grid algorithm for replicated data
Information Processing Letters
A N algorithm for mutual exclusion in decentralized systems
ACM Transactions on Computer Systems (TOCS)
Data communication and replication strategies for large scale distributed databases
Data communication and replication strategies for large scale distributed databases
Read-only transactions in a distributed database
ACM Transactions on Database Systems (TODS)
Consistency and recovery control for replicated files
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An efficient, fault-tolerant protocol for replicated data management
PODS '85 Proceedings of the fourth ACM SIGACT-SIGMOD symposium on Principles of database systems
Benchmark Handbook: For Database and Transaction Processing Systems
Benchmark Handbook: For Database and Transaction Processing Systems
Replication Techniques in Distributed Systems
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Transaction Processing: Concepts and Techniques
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Weighted voting for replicated data
SOSP '79 Proceedings of the seventh ACM symposium on Operating systems principles
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SOSP '81 Proceedings of the eighth ACM symposium on Operating systems principles
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ICSE '76 Proceedings of the 2nd international conference on Software engineering
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IEEE Concurrency
Fine Grained Replication in Distributed Databases: A Taxonomy and Practical Considerations
DEXA '00 Proceedings of the 11th International Conference on Database and Expert Systems Applications
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CIS'04 Proceedings of the First international conference on Computational and Information Science
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PDCAT'04 Proceedings of the 5th international conference on Parallel and Distributed Computing: applications and Technologies
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The article proposes a scalable protocol for replication management in large-scale replicated systems. The protocol organizes sites and data replicas into a tree-structured, hierarchical cluster architecture. The basic idea of the protocol is to accomplish the complex task of updating replicated data with a very large number of replicas by a set of related but independently committed transactions. Each transaction is responsible for updating replicas in exactly one cluster and invoking additional transactions for member clusters. Primary copies (one from each cluster) are updated by a cross-cluster transaction. Then each cluster is independently updated by a separate transaction. This decoupled update propagation process results in possible multiple views of replicated data in a cluster. Compared to other replicated data management protocols, the proposed protocol has several unique advantages. First, thanks to a smaller number of replicas each transaction needs to atomically update in a cluster, the protocol significantly reduces the transaction abort rate, which tends to soar in large transactional systems. Second, the protocol improves user-level transaction response time as top-level update transactions are allowed to commit before all replicas have been updated. Third, read-only queries have the flexibility to see database views of different degrees of consistency and data currency. This ranges from global, most up to date, and consistent views, to local, consistent, but potentially old views, to local, nearest to users but potentially inconsistent views. Fourth, the protocol maintains its scalability by allowing dynamic system reconfiguration as it grows by splitting a cluster into two or more smaller ones. Fifth, autonomy of the clusters is preserved as no specific protocol is required to update replicas within the same cluster. Clusters are, therefore, free to use any valid replication or concurrency control protocols.