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Small Profits and Quick Returns: A Practical Social Welfare Maximizing Incentive Mechanisms for Deadline-sensitive Tasks in Crowdsourcing

This is python code for the paper work published in IEEE Internet of Things Journal. You can access to the paper through this link.

Prerequisites

  • Language: Python
  • Required Packages: numpy, pandas, matplotlib, munkres
  • To install the required packages, type the following command:
  1. Python 2
pip install numpy pandas matplotlib munkres
  1. Python 3
pip3 install numpy pandas matplotlib munkres

Running the code

  • Class 'task': task.py, Class 'provider' or 'worker': provider.py, and Class 'platform': platform.py
  • Since some of simulations may take quite a long time, simulation results are attached in 'data' directory.
  1. Visualization of the behavior of task
python3 task_figure.py
  1. Visualization of the punctual behavior of worker
python3 provider_figure.py
  1. Simulation for optimal task-worker matching
python3 optimal_run.py
  1. Visualization of the results of 3)
python3 optimal_visualization.py
  1. Simulation for one time competition between our work and the benchmark
python3 capacity_run.py
  1. Visualization of the results from 5)
python3 capacity_visualization.py
  1. Simulation for reselection process which consider the movement of workers and tasks between two platforms
python3 reselection.py
  1. Visualization of the results from 7)
python3 reselection_visualization.py
  1. Simulation for multiple reselection process which converges to balance point
python3 reselection_multiple_round.py
  1. Visualization of the results from 9)
python3 reselection_multiple_round_visualization.py
  1. Simulation for parameter setting
python3 parameter_run.py
  1. Visualization of the results from 11)
python3 parameter_visualization.py

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Seek Help

Hello, I am a postgraduate student, and I saw your message on GitHub:Small Profits and Quick Returns: A Practical Social Welfare Maximizing Incentive Mechanisms for Deadline-sensitive Tasks in Crowdsourcing.But the data in the paper was encrypted,Some code needs to look at the data to help understand it.I hope you can provide me with the data, which will be of great help to my research. Thank you very much!

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