Cooperative shared memory: software and hardware for scalable multiprocessors
ACM Transactions on Computer Systems (TOCS)
Parallel database systems: open problems and new issues
Distributed and Parallel Databases - Special issue: Research topics in distributed and parallel databases
Holistic schedulability analysis for distributed hard real-time systems
Microprocessing and Microprogramming - Parallel processing in embedded real-time systems
Principles of distributed database systems (2nd ed.)
Principles of distributed database systems (2nd ed.)
Fault-tolerant broadcasts and related problems
Distributed systems (2nd Ed.)
Replica Consistency in Lazy Master Replicated Databases
Distributed and Parallel Databases
Parallel Processing with Autonomous Databases in a Cluster System
On the Move to Meaningful Internet Systems, 2002 - DOA/CoopIS/ODBASE 2002 Confederated International Conferences DOA, CoopIS and ODBASE 2002
A FIFO worst case analysis for a hard real-time distributed problem with consistency constraints
ICDCS '97 Proceedings of the 17th International Conference on Distributed Computing Systems (ICDCS '97)
Preventive Replication in a Database Cluster
Distributed and Parallel Databases
Apuama: combining intra-query and inter-query parallelism in a database cluster
EDBT'06 Proceedings of the 2006 international conference on Current Trends in Database Technology
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We consider the use of a cluster system for Application Service Providers. To obtain high-performance and high-availability, we replicate databases (and DBMS) at several nodes, so they can be accessed in parallel through applications. Then the main problem is to assure the consistency of autonomous replicated databases. Preventive replication [8] provides a good solution that exploits the cluster's high speed network, without the constraints of synchronous replication. However, the solution in [8] assumes full replication and a restricted class of transactions. In this paper, we address these two limitations in order to scale up to large cluster configurations. Thus, the main contribution is a refreshment algorithm that prevents conflicts for partially replicated databases. We describe the implementation of our algorithm over a cluster of 32 nodes running PostGRESQL. Our experimental results show that our algorithm has excellent scale up and speed up.