Replica placement for high availability in distributed stream processing systems
Proceedings of the second international conference on Distributed event-based systems
Distributed middleware reliability and fault tolerance support in system S
Proceedings of the 5th ACM international conference on Distributed event-based system
SEM'04 Proceedings of the 4th international conference on Software Engineering and Middleware
Probabilistically bounded staleness for practical partial quorums
Proceedings of the VLDB Endowment
Toward a principled framework for benchmarking consistency
HotDep'12 Proceedings of the Eighth USENIX conference on Hot Topics in System Dependability
Dynamic Synchronous/Asynchronous Replication
ACM Transactions on Storage (TOS)
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A dependable middleware should be able to adaptively share the distributed resources it manages in order to meet diverse application requirements, even when the quality of service (QoS) is degraded due to uncertain variations in load and unanticipated failures. We have addressed this issue in the context of a dependable middleware that adaptively manages replicated servers to deliver a timely and consistent response to time-sensitive client applications. These applications have specific temporal and consistency requirements, and can tolerate a certain degree of relaxed consistency in exchange for better response time. We propose a flexible QoS model that allows clients to specify their timeliness and consistency constraints. We also propose an adaptive framework that dynamically selects replicas to service a client's request based on the prediction made by probabilistic models. These models use the feedback from online performance monitoring of the replicas to provide probabilistic guarantees for meeting a client's QoS specification. The experimental results we have obtained demonstrate the role of feedback and the efficacy of simple analytical models for adaptively sharing the available replicas among the users under different workload scenarios.