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Temporal violations may often take place and deteriorate the overall QoS of scientific workflows. To handle temporal violations in an automatic and cost-effective fashion, we need to resolve the following issues: 1) how to define fine-grained recoverable temporal violations, 2) which light-weight effective exception handling strategies to be facilitated. This paper proposes an effective exception handling framework. Based on a probability based temporal consistency model, the probability range for recoverable temporal violations is divided into three levels of fine-grained temporal violations. Afterwards, three corresponding light-weight exception handling strategies including TDA (Time Deficit Allocation), ACOWR (Ant Colony Optimisation based two-stage Workflow local Rescheduling) and TDA+ACOWR (the combined strategy of TDA and ACOWR) are presented. The experimental results demonstrate the excellent performance of our framework in reducing both local and global temporal violations.