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In this paper, the authors explore the use of provenance for analyzing execution dynamics in distributed systems. They argue that provenance could have significant practical benefits for system administrators, e.g., for reasoning about changes in a system's state, diagnosing protocol misconfigurations, detecting intrusions, and pinpointing performance bottlenecks. However, to realize this vision, they must revisit several aspects of provenance management. As a first step, they present Time-Aware Provenance (TAP), an enhanced provenance model that explicitly represents time, distributed state, and state changes. They outline the research agenda towards developing novel query processing, languages, and optimization techniques that can be used to efficiently and securely query time-aware provenance, even in the presence of transient state or untrusted nodes.
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