/Huang11-implementation

This repository contains Python implementation of Huang11 quantile computation algorithm

Primary LanguageJupyter Notebook

Huang11 Algorithm

Author: Artem Bakhanov. email

This project is Assignment 1 of STDS course at Innopolis University.

Project structure

If you just want to see that the algorithm is working go to example.ipynb. If you want to see network cost complexity analysis go to performance.ipynb.

.
├── README.md                       # project description      
├── example.ipynb                   # usage example
├── generator.py                    # random network generator
├── helper.py                       # auxillary functions
├── main.py                         # just random file
├── message.py                      # network message classes
├── network.py                      # network implementation
├── node.py                         # node classes
├── performance.ipynb               # testing performance
├── requirements.txt                # python requirements
├── result.py                       # result classes, merge methods
├── task.py                         # task class for nodes
└── test_complexity.py              # file for testing for complexity

References

  1. Z. Huang, L. Wang, K. Yi, and Y. Liu, “Sampling based algorithms for quantile computation in sensor networks,” in Proceedings of the 2011 ACM SIGMOD International Conference on Management of data, 2011, pp. 745–756.
  2. Z. Chen and A. Zhang, “A survey of approximate quantile computation on large-scale data,” IEEE Access, vol. 8, pp. 34 585–34 597, 2020.