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Designed and Implemented an algorithm using Java and Python which efficiently and continuously infers VM needs and meets them appropriately using Docker containers.

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Efficient Algorithm for Dynamic Inference of Virtual Machine Resource Needs

These instructions will get you a copy of the project running up and running on your local machine for development and testing purposes.

Prerequisites

Docker should be installed on your local machine. The steps to install a Docker can be found at https://docs.docker.com/engine/installation/ Python should be installed on your local machine. It can be downloaded from https://www.python.org/downloads/

File List

  1. ccalog.py # Our proposed algorithm written in Python
  2. primality_testing.cpp # Program checks if a number is prime or not. Returns 1 or 0 based on whether the threshold limit has been reached or not
  3. inp.txt # Contains randomly generated numbers.
  4. driver.sh # Concatenates the inp.txt file and primality_testing.cpp

Installation

We have made the Docker Image public. It can be downloaded by running the following command docker pull rohansumant/ccproject2

Running the tests

After pulling the image, run the ccalgo.py program from the terminal. python ccalgo.py The output of the program can be seen on the terminal.

Authors

  • Netra Agrawal
  • Rohan Sumant
  • Chetan Pangam
  • Sai Lalitha Sree Vuddamarry

Acknowledgement

We thank Abhishek Gupta, Professor for COEN 241 Cloud Computing course at Santa Clara University for the support and guidance throughout the project.

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Designed and Implemented an algorithm using Java and Python which efficiently and continuously infers VM needs and meets them appropriately using Docker containers.

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  • Java 59.3%
  • Python 40.7%