Checkpointing and Rollback-Recovery for Distributed Systems
IEEE Transactions on Software Engineering - Special issue on distributed systems
Principles of distributed database systems (2nd ed.)
Principles of distributed database systems (2nd ed.)
A Formal Characterization of Epsilon Serializability
IEEE Transactions on Knowledge and Data Engineering
Fast Algorithms for Maintaining Replica Consistency in Lazy Master Replicated Databases
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Improving Performance in Replicated Databases through Relaxed Coherency
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Fine-grained replication and scheduling with freshness and correctness guarantees
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Preventive Replication in a Database Cluster
Distributed and Parallel Databases
Automatic methods for predicting machine availability in desktop Grid and peer-to-peer systems
CCGRID '04 Proceedings of the 2004 IEEE International Symposium on Cluster Computing and the Grid
MIDDLE-R: Consistent database replication at the middleware level
ACM Transactions on Computer Systems (TOCS)
Concurrency and Computation: Practice & Experience - Adaptive Grid Middleware
The leganet system: Freshness-aware transaction routing in a database cluster
Information Systems
Middleware-based database replication: the gaps between theory and practice
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Lifetime-based dynamic data replication in P2P systems
Globe'11 Proceedings of the 4th international conference on Data management in grid and peer-to-peer systems
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In distributed systems, replication is used for ensuring availability and increasing performances. However, the heavy workload of distributed systems such as web2.0 applications or Global Distribution Systems, limits the benefit of replication if its degree (i.e., the number of replicas) is not controlled. Since every replica must perform all updates eventually, there is a point beyond which adding more replicas does not increase the throughput, because every replica is saturated by applying updates. Moreover, if the replication degree exceeds the optimal threshold, the useless replica would generate an overhead due to extra communication messages. In this paper, we propose a suitable replication management solution in order to reduce useless replicas. To this end, we define two mathematical models which approximate the appropriate number of replicas to achieve a given level of performance. Moreover, we demonstrate the feasibility of our replication management model through simulation. The results expose the effectiveness of our models and their accuracy.