This paper investigates the use of partial replication in the Database State Machine approach introduced earlier for fully replicated databases. It builds on the order and atomicity properties of group communication primitives to achieve strong consistency and proposes two new abstractions: Resilient Atomic Commit and Fast Atomic Broadcast. Even with atomic broadcast, partial replication requires a termination protocol such as atomic commit to ensure transaction atomicity. With Resilient Atomic Commit our termination protocol allows the commit of a transaction despite the failure of some of the participants. Preliminary performance studies suggest that the additional cost of supporting partial replication can be mitigated through the use of Fast Atomic Broadcast.
Total order multicast greatly simplifies the implernentation of fault-tolerant services using the replicated state machine approach. The additional latency of total ordering can be masked by taking advantage of spontaneous ordering observed in U N s : A tentative delivery allows the application to proceed in parallel with the ordering protocol.The effectiveness of rhe technique rests on the optimistic assumption that a large share of correctly ordered tentative deliveries offsets the cost of undoing the effect of mistakes. This paper proposes a simple technique which enables the usage of optimistic delivery also in WANs with much larger transmission delays where the optimistic assumption does not normally hold. Ourpmposal exp1oit.s local clocks and the stability of network delays to reduce the mistakes in the ordering of tentative deliveries. An experimental evaluation of a modified sequencer-based pmtocol is przsented, illustraring the usefulness of the approach in fault-tolerant database management.
Several techniques for database replication using group communication have recently been proposed, namely, the Database State Machine, Postgres-R, and the NODO protocol. Although all rely on a totally ordered multicast for consistency, they differ substantially on how multicast is used. This results in different performance trade-offs which are hard to compare as each protocol is presented using a different load scenario and evaluation method.In this paper we evaluate the suitability of such protocols for replication of On-Line Transaction Processing (OLTP) applications in clusters of servers and over wide area networks. This is achieved by implementing them using a common infra-structure and by using a standard workload. The results allows us to select the best protocol regarding performance and scalability in a demanding but realistic usage scenario.
Database replication based on group communication systems has recently been proposed as an efficient and resilient solution for large-scale data management. However, its evaluation has been conducted either on simplistic simulation models, which fail to assess concrete implementations, or on complete system implementations which are costly to test with realistic large-scale scenarios. This paper presents a tool that combines implementations of replication and communication protocols under study with simulated network, database engine, and traffic generator models. Replication components can therefore be subjected to realistic large scale loads in a variety of scenarios, including fault-injection, while at the same time providing global observation and control. The paper shows first how the model is configured and validated to closely reproduce the behavior of a real system, and then how it is applied, allowing us to derive interesting conclusions both on replication and communication protocols and on their implementations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.