This repository contains the source code for a system that optimizes the distribution of cache video files in a server network, as presented in the Google Hashcode 2017 problem. The system is designed to minimize the average waiting time for all requests by strategically placing cached video files on servers and data centers based on anticipated user requests and network latencies.
The problem at hand is to optimize the distribution of cache video files in a server network in order to minimize the average waiting time for all requests, as presented in Google Hashcode 2017. We are given the following information:
- The video files that will be requested, and the quantities associated with each endpoint.
- The latencies between all endpoints, servers, and data centers.
Google Hashcode is an annual programming competition organized by Google for students and professionals across Europe, the Middle East, and Africa. Participants are given four hours to process a large dataset, find solutions to a problem, and upload their solutions to the judge system. The goal of the competition is to encourage the development of innovative and efficient algorithms for solving real-world problems.
This implementation has a built-in judge system which works as described in the task docs and shows the scores for each individual file at the end.
| File Name | Score |
|---|---|
| me_at_the_zoo.txt | 512283 |
| trending_today.txt | 499966 |
| videos_worth_spreading.txt | 620838 |
| kittens.txt | 907731 |
Score = 2540819
Solution files can be found in the `solution
.idea: configuration files for the JetBrains PyCharm IDEData: input data provided by Google for the problemProblem: folder containing a PDF file describing the problemSolutions: output data that represent the final solutionsrc/code: source code used to generate the solutionGoogle Hashcode 2017 Qualification.iml: configuration file for the JetBrains PyCharm IDEREADME.md: this file containing information about the repository and its contents