Abstract
To achieve on-time completion of time-constrained business cloud workflows, a large number of parallel cloud workflow instances need to be constantly monitored so that temporal violations (namely intermediate runtime delays) can be detected and handled timely. Over the last few years, many strategies have been proposed but they are not adaptive enough to capture the dynamic behaviors of business cloud workflows. In this paper, we introduce the idea of “adaptiveness” into our strategy design. Specifically, we first present an adaptive temporal checkpoint selection strategy where the time intervals between checkpoints are adaptively determined at runtime, and then propose a matching temporal violation handling strategy which can determine the required lifecycle of cloud services. The evaluation results demonstrate that our adaptive strategy can achieve both higher efficiency and better cost effectiveness compared with conventional strategies.
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