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Fig 1.

Edge-cloud collaborative processing framework.

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Fig 2.

Architecture of the edge-cloud collaborative IoT data processing system.

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Fig 3.

Overall flow of the NAG algorithm.

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Fig 4.

Overall process of the CDAG algorithm.

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Table 1.

Parameter setting.

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Fig 5.

Results of searching performance of different algorithm models on the Sphere function and Griewank function.

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Fig 6.

Results of searching performance of different algorithm models on the Rosenbrock function, Ackley function, and Rastrigin function.

Note: Fig 6-A shows the results on Rosenbrock function; Fig 6-B represents results on Ackley function; Fig 6-C is presents results on Rastrigin function.

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Fig 7.

Results of searching performance of the improved NAG algorithm on Sphere function and Griewank function.

Note: Fig 7-A represents the results on Sphere function; Fig 7-B represents the results on Griewank function.

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Fig 8.

Results of searching performance of the improved NAG algorithm on Rosenbrock function, Ackley function, and Rastrigin function.

Note: Fig 8-A represents the results on Rosenbrock function; Fig 8-B represents the results on Ackley function; Fig 8-C represents the results on Rastrigin function.

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Fig 9.

Comparison of stimulation results of different models.

Note: Fig A-C represent the comparison of different models in economic cost, load balancing and completion time.

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Fig 10.

Delay performance under different schemes.

Note: Fig 10-A gives the communication delay performance of models under different scheduling; Fig 10-B represents the calculation delay performance of models under different scheduling; Fig 10-C provides the standardized communication delay under different pressures.

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Fig 11.

Effect analysis of the IoT analysis platform via edge-cloud collaboration.

Note: Fig 11-A is the comparison of time-consuming between the cloud platform and edge-cloud collaborative platform. Fig 11-B shows the comparison of time-consuming between the cloud platform and edge-cloud collaborative platform in the case of 20 rules of single device. Fig 11-C represents the comparison of time-consuming between the cloud platform and edge-cloud collaborative platform in the case of large resource load. Fig D is the experimental results of bandwidth occupation.

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Fig 12.

Performance of different models in different data sets.

Note: Fig 12-A shows the reliability test results of the scales of different dimensions, and Fig 12-B indicates the reliability test results of the actual indicators.

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Fig 13.

Fitting analysis results of the model performance in different data sets.

Note: Fig 13-A represents the fitting indexes of CFA of career planning; Fig 13-B shows the fitting indexes of CFA of organizational support; Fig 13-C indicates the fitting indexes of CFA of career maturity; Fig 13-D shows the fitting indexes of CFA of the overall scale model.

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Table 2.

Descriptive statistical analysis results of each variable.

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Table 3.

Correlation statistical anWEalysis results of each variable.

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