Published February 18, 2025 | Version v1

Various Datasets Accompanying the Paper "Infusing Formal Methods into Ops-related Practices: Case Studies in Resource Allocation in the Cloud"

  • 1. ROR icon West University of Timişoara

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Description

Various datasets accompagnig  the paper Infusing Formal Methods into Ops-related Practices: Case Studies in Resource Allocation in the Cloud. The code used for generating them and how to use them is available at here.

  • TrainingDatasets.zip contains datasets for 4 use cases. More details about the properties of the dataset is in the paper, Section 3.3.
  • GNNModels.zip contains datasets, for each of the 4 use cases, with graph neural networks trained using the above datasets with the architectures and hyperparameters as specified in the paper, Sections 4.1 and 5.2.
  • SMT-LIB.zip contains datasets, for each of the 4 use cases, with constrained optimization problems in the SMT-LIB format augumented with soft constraints extracted from GNN predictions as discussed in the paper, Sections 4.2 and 5.3.
  • StatDataFromSMT-LIB.zip contain datasets, for each of the 4 use cases, used for drafting the conclusions for the 3 research questions in the paper. The data is extracted from the SMT-LIB files above and contains information like Samples, Epochs, Batchsize, Offers, Type, Time, Price which is then used to draw the conclusions for RQ1-3.

Files

GNNModels.zip

Files (71.2 MB)

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md5:5cf652a0f3160055481088dd6f4498d3
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md5:ae3fdfc1861f946bcdc600fe1b82192e
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md5:09d994fc4d1955d22e3635a9cfb683d6
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md5:23b61230206677d0e14a9b4c6f0ac6b1
42.9 MB Preview Download

Additional details

Funding

Unitatea Executiva Pentru Finantarea Invatamantului Superior a Cercetarii Dezvoltarii si Inovarii
SAGE: A Symbiosis of Satisfiability Checking, Graph Neural Networks and Symbolic Computation PN-III-P1-1.1-TE-2021-0676

Software