Serializability theory for replicated databases

Bernstein, P. A.; Goodman, Nathan

doi:10.1016/0022-0000(85)90058-3

Cited by 42 publications

(10 citation statements)

References 14 publications

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“…By removing the constraint that FRSG(H), contains SG(H), an if and only if version of the theorem can be obtained (see [4]). However, since all practical schedulers we know of produce acyclic SGs, the only-if direction is of theoretical interest only.…”

Section: Serialization Graphs For Rd Historiesmentioning

confidence: 97%

“…Condition (3) states that a transaction may not read a copy unless it has been previously initialized. And Condition (4) states that the history records the execution order of noncommutative operations.…”

Section: Replicated Data Historiesmentioning

confidence: 99%

“…However, these operations do not affect the values of data items read or written, and so do not affect the semantics of the history. 4 Step (3) also transforms a Read of a data item from a noninitial IN, IN(x,), into a Read of the copy, Xb, read by IN(x,). By the extended definition of equivalence above, this too preserves equivalence.…”

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confidence: 99%

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A proof technique for concurrency control and recovery algorithms for replicated databases

Bernstein¹,

Goodman²

1987

Distrib Comput

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Abstract. A replicated database is a distributed database in which copies of some data items are stored redundantly at multiple sites. In such a system, an execution of transactions is correct if it is equivalent to a serial execution of those transactions on a one copy database. We show that in any serializable execution, if all transactions see the failures and recoveries of data item copies in a consistent order, then the execution is correct. We model this condition using a modified type of serialization graph, and show that if this graph is acyclic then the corresponding execution is correct. We demonstrate the value of this model by using it to prove the correctness of an algorithm for synchronizing access to a replicated database.

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Section: Serialization Graphs For Rd Historiesmentioning

confidence: 97%

Section: Replicated Data Historiesmentioning

confidence: 99%

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A proof technique for concurrency control and recovery algorithms for replicated databases

Bernstein¹,

Goodman²

1987

Distrib Comput

Self Cite

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“…We call a client request a "transaction" both in the TR and SM scheme. A replicated service (or database) satisfies one-copy serializability (1SR) [8]: transactions performed on the replicas have an ordering which is equivalent to an ordering obtained when the transactions are performed sequentially in a single centralized database.…”

Section: Analytical Modelmentioning

confidence: 99%

“…Thus, it is important to remember that some services can be replicated using SM but not TR. Hence, our comparison is valid only for replicated services, in which concurrent requests satisfy one-copy serializability [8]. We also assume the crashrecovery model of failure, in which N/2 − 1 server crashes can be tolerated, where N is the number of servers.…”

Section: Introductionmentioning

confidence: 99%

Model-Driven Comparison of State-Machine-Based and Deferred-Update Replication Schemes

Wojciechowski

Kobus

Kokociński

2012

2012 IEEE 31st Symposium on Reliable Distributed Systems

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Abstract-In this paper, we analyze and experimentally compare state-machine-based and deferred-update (or transactional) replication, both relying on atomic broadcast. We define a model that describes the upper and lower bounds on the execution of concurrent requests by a service replicated using either scheme. The model is parametrized by the degree of parallelism in either scheme, the number of processor cores, and the type of requests. We analytically compared both schemes and a nonreplicated service, considering abcast-and request-executiondominant workloads. To evaluate transactional replication experimentally, we developed Paxos STM-a novel fault-tolerant distributed software transactional memory with programming constructs for transaction creation, abort, and retry. For statemachine-based replication, we used JPaxos. Both systems share the same implementation of atomic broadcast based on the Paxos algorithm. We present the results of performance evaluation of both replication schemes, and a non-replicated (thus prone to failures) service, considering various workloads. The key result of our theoretical and experimental work is that neither system is superior in all cases. We discuss these results in the paper.

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Simplifying the Design of Knowledge-Based Algorithms Using Knowledge Consistency

Neiger

1995

Information and Computation

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Serializability theory for replicated databases

Cited by 42 publications

References 14 publications

A proof technique for concurrency control and recovery algorithms for replicated databases

A proof technique for concurrency control and recovery algorithms for replicated databases

Model-Driven Comparison of State-Machine-Based and Deferred-Update Replication Schemes

Simplifying the Design of Knowledge-Based Algorithms Using Knowledge Consistency

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