PaxonDHT: achieving consensus in distributed hash tables

Temkow, B.; Bosneag, Anne-Marie; Li, Xinjie; Brockmeyer, Monica

doi:10.1109/saint.2006.48

Cited by 7 publications

(5 citation statements)

References 19 publications

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“…These protocols protect the underlying data from many types of faults, such as node failures, dishonest and misbehaving nodes, network partitions or even predictive failures due to maintenance. Several consensus protocols and variants are available in the historical bibliography [44]- [46]. These sometimes proved to be more difficult to implement than originally anticipated [47] and even harder if byzantine faults [12] are considered.…”

Section: A Consensus Protocolsmentioning

confidence: 99%

A Performant Protocol for Distributed Health Records Databases

2021

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Electronic Health Records (EHR) have a distributed nature and can be managed by distinct affinity domains. Sharing patient health information across distinct organisations helps to deliver a wellinformed diagnosis, improving the quality of healthcare service. The federation of those information systems can take the form of a distributed database where data are partitioned and possibly replicated across distinct computational systems. However, the benefits of having a distributed system, such as consistency, availability, and data protection, are mostly absent. This article proposes a distributed database consensus protocol designed to improve the performance of EHR insertion operations, a particularly critical issue in medical imaging cases due to the data volume. It explores the personal and non-transferable nature of EHR and the proposed methodology reduces the data contention through data isolation, improving the overall retrieval performance and detection of misbehaving parties. Furthermore, the proposal follows the recent European General Data Protection Regulation (GDPR), which states that appropriate mechanisms should be used in order to protect data against accidental loss, destruction, or damage, using appropriate technical or organisational measures.INDEX TERMS blockchain, consensus protocol, distributed ledger, distributed databases, electronic health records

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Section: A Consensus Protocolsmentioning

confidence: 99%

A Performant Protocol for Distributed Health Records Databases

2021

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“…PaxonDHT [23] proposes a solution for implementing Paxos consensus algorithm [10] on top of a DHT as a basic block for active replication. However, PaxonDHT only ensures the safety of Paxos with some probability because group membership changes are not synchronized with the run of consensus instances.…”

Section: Related Workmentioning

confidence: 99%

Semias: Self-Healing Active Replication on Top of a Structured Peer-to-Peer Overlay

Costache

Ropars

Morin

2010

2010 29th IEEE Symposium on Reliable Distributed Systems

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Active replication on top of a structured peer-to-peer overlay is an attractive solution for transparently providing high availability to distributed applications. However, self-healing is necessary to ensure the availability of the replicated application despite node arrivals, failures or departures in the overlay. Selfhealing means to automatically reconfigure the replica groups when changes in the overlay occur. In the case of active replication, reconfigurations must be done carefully, to keep the replicas consistency. Moreover, as every reconfiguration could imply a state transfer between replicas, their number should be limited. In this paper we propose a self-healing solution that limits the number of group reconfigurations and ensures the availability of the replicated application in a dynamic environment. To evaluate the performance of our solution, we implemented it in a framework, called Semias, in the context of Vigne grid middleware. Experiments run on Grid'5000 and PlanetLab show the performance of the framework and the efficiency of our selfhealing mechanisms in a dynamic environment.

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“…In [11] Paxos is used to achieve consensus in DHTs. The authors present a middleware service called PaxonDHT, which provides a mean to guarantee strong consistency among a set or replicas.…”

Section: Related Workmentioning

confidence: 99%

Atomic Commitment in Transactional DHTs

Moser

Haridi

2007

Towards Next Generation Grids

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We investigate the problem of atomic commit in transactional database systems built on top of Distributed Hash Tables. Therefore we present a framework for DHTs to provide strong data consistency and transactions on data stored in a decentralized way. To solve the atomic commit problem within distributed transactions, we propose to use an adaption of Paxos commit as a non-blocking algorithm. We exploit the symmetric replication technique existing in the DKS DHT to determine which nodes are necessary to execute the commit algorithm. By doing so, we achieve a lower number of communication rounds in contrast to applying traditional Three-Phase-Commit protocols. We also show how the proposed solution can cope with dynamism due to churn in DHTs. Our solution works correctly relying only on an inaccurate failure detection of node failure, what is necessary for systems running over the Internet.

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PaxonDHT: achieving consensus in distributed hash tables

Cited by 7 publications

References 19 publications

A Performant Protocol for Distributed Health Records Databases

A Performant Protocol for Distributed Health Records Databases

Semias: Self-Healing Active Replication on Top of a Structured Peer-to-Peer Overlay

Atomic Commitment in Transactional DHTs

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