task scheduling
These datasets of synthetic workflows (task graphs) were generated to evaluate the performance and scalability of a multi-objective and multi-constrained scheduling approach for workflow applications of various structures, sizes, and sensing/actuating requirements in a cyber-physical system (CPS) based on the edge-hub-cloud paradigm.
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Alibaba Cluster Trace (cluster-trace-v2018) . The dataset comprises metadata and runtime information concern-ing 4K machines, 71K online services, and 4M batch jobs over an 8-day horizon. Compared with the cluster-trace-v2017 dataset, this dataset features a longer sampling period, a larger number of workloads, and more fine-grained directed acyclic graph (DAG) dependency information.
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