Abstract

AbstractCheckpointing has a crucial impact on systems' performance and fault‐tolerance effectiveness: excessive checkpointing results in performance degradation, while deficient checkpointing incurs expensive recovery. In distributed systems with independent checkpoint activities there is no easy way to determine checkpoint frequencies optimizing response‐time and fault‐tolerance costs at the same time. The purpose of this paper is to investigate the potentialities of a statistical decision‐making procedure. We adopt a simulation‐based approach for obtaining performance metrics that are afterwards used for determining a trade‐off between checkpoint interval reductions and efficiency in performance. Statistical methodology including experimental design, regression analysis and optimization provides us with the framework for comparing configurations, which use possibly different fault‐tolerance mechanisms (replication‐based or message‐logging‐based). Systematic research also allows us to take into account additional design factors, such as load balancing. The method is described in terms of a standardized object replication model (OMG FT‐CORBA), but it could also be applied in other (e.g. process‐based) computational models. Copyright © 2006 John Wiley & Sons, Ltd.

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