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On-time completion is one of the most important QoS (Quality of Service) dimensions for business processes running in the cloud. While today’s business systems often need to handle thousands of concurrent user requests, process monitoring is basically conducted in a one by one fashion. It is possible to repeat the strategies for monitoring a single process a thousand times to monitor a thousand parallel processes. However, the time overhead will be a thousand-fold increase as well, which brings a big challenge for process monitoring. In this paper, based on a novel runtime throughput consistency model, we propose a QoS-aware throughput based checkpoint selection strategy which can dynamically select a small number of checkpoints along the system timeline to facilitate the temporal verification of throughput constraints and achieve the target on-time completion rate. The experimental results demonstrate that our strategy can achieve the best efficiency and effectiveness compared with the state-of-the-art as well as other representative response-time based checkpoint selection strategies.
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Stored only when both papers are in the corpus — 15 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.