Chain replication in theory and in practice

Fritchie, Scott Lystig

doi:10.1145/1863509.1863515

Cited by 9 publications

(4 citation statements)

References 12 publications

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“…The reply for every query request is generated by the tail and sent to the client. Since all the values stored in the tail are guaranteed to have been propagated to all replicas, reads are always consistent [36].…”

Section: Chain Replicationmentioning

confidence: 99%

“…Their main objective is to improve replication cell performance by distributing consistency management responsibilities among servers. These approaches include different variants of Paxos such as Multi-Paxos [16 and 17], Fast Paxos [27], Mencius [28], generalized Paxos [29], EPaxos [30], Object Ownership Distribution (OOD) [13], and chain replication [32][33][34][35][36].…”

Section: Related Workmentioning

confidence: 99%

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Bidirectional Chain Replication for Higher Throughput Provision

2019

KSII TIIS

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Provision of higher throughput without sacrificing consistency guarantees in replication systems is a critical problem. In this paper, we propose a novel approach called Bidirectional Chain Replication (BCR) to improve throughput in traditional Chain Replication (CR) through better utilization of computing and communication resources of the chain. Unlike CR where the whole replicated data store is treated as a single unit, in BCR the replicated shared data at each server in the chain is split into two disjoint Logical Partitions (LP 1 , LP 2). This forms two chains running concurrently on the same hardware in two opposite directions; the first chain (CR 1) exclusively manipulates data objects in LP 1 , while the second chain (CR 2) exclusively manipulates data objects in LP 2 , therefore, conflict is avoided and concurrency is guaranteed. The simultaneous employment of these two chains results in better utilization of hardware in the sense that the two chains can evenly share the workload, hence, throughput can be improved without sacrificing consistency. Experimental results showed an improvement of approximately 85% in throughput of BCR over CR.

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Section: Chain Replicationmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Bidirectional Chain Replication for Higher Throughput Provision

2019

KSII TIIS

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“…The Chain Replication repair technique used by HibariDB [7] starts a repair with a transition from chain…”

Section: Chain Repairmentioning

confidence: 99%

Testing and Verifying Chain Repair Methods for Corfu Using Stateless Model Checking

Aronis

Fritchie

Sagonas

2017

Lecture Notes in Computer Science

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Abstract. CORFU is a distributed shared log that is designed to be scalable and reliable in the presence of failures and asynchrony. Internally, CORFU is fully replicated for fault tolerance, without sharding data or sacrificing strong consistency. In this case study, we present the modeling approaches we followed to test and verify, using Concuerror, the correctness of repair methods for the Chain Replication protocol suitable for CORFU. In the first two methods we tried, Concuerror located bugs quite fast. In contrast, the tool did not manage to find bugs in the third method, but the time this took also motivated an improvement in the tool that reduces the number of traces explored. Besides more details about all the above, we present experiences and lessons learned from applying stateless model checking for verifying complex protocols suitable for distributed programming.

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“…This reduces the number of replicas necessary, not only increasing efficiency but also robustness in the face of limited sources of diversity. Our protocols are based on Chain Replication [10], which is increasingly being used in scalable fault tolerant systems [17][18][19][20]. Chain Replication also uses an external configuration service, but cannot tolerate even general crash failures as the protocol depends on accurate failure detection, an overly strong requirement in today's datacenters.…”

Section: Introductionmentioning

confidence: 99%

Byzantine Chain Replication

Renesse

Schiper

2012

Lecture Notes in Computer Science

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Abstract. We present a new class of Byzantine-tolerant State Machine Replication protocols for asynchronous environments that we term Byzantine Chain Replication. We demonstrate two implementations that present different trade-offs between performance and security, and compare these with related work. Leveraging an external reconfiguration service, these protocols are not based on Byzantine consensus, do not require majoritybased quorums during normal operation, and the set of replicas is easy to reconfigure. One of the implementations is instantiated with t + 1 replicas to tolerate t failures and is useful in situations where perimeter security makes malicious attacks unlikely. Applied to in-memory BerkeleyDB replication, it supports 20,000 transactions per second while a fully Byzantine implementation supports 12,000 transactions per second-about 70% of the throughput of a non-replicated database.

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Chain replication in theory and in practice

Cited by 9 publications

References 12 publications

Bidirectional Chain Replication for Higher Throughput Provision

Bidirectional Chain Replication for Higher Throughput Provision

Testing and Verifying Chain Repair Methods for Corfu Using Stateless Model Checking

Byzantine Chain Replication

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