This repository maintains the implementation of an adaptive matrix factorization approach to online QoS prediction of cloud services, which has been published in ICDCS'2014.

Read more information from our paper:

Jieming Zhu, Pinjia He, Zibin Zheng, and Michael R. Lyu, "Towards Online, Accurate, and Scalable QoS Prediction for Runtime Service Adaptation," in Proc. of the 34th IEEE International Conference on Distributed Computing Systems (ICDCS), 2014. [Paper]

Dependencies

• Python 2.7 (https://www.python.org)
• Cython 0.20.1 (http://cython.org)
• numpy 1.8.1 (http://www.scipy.org)
• scipy 0.13.3 (http://www.scipy.org)

Usage

The AMF algorithm is implemented in C++ and further wrapped up as a python package for common use.

1. Install AMF package

   Download the repo: git clone https://github.com/wsdream/AMF.git,

   (Optionally) Check out branch: git checkout icdcs14-python,

   Then install the package python setup.py install --user.

2. Change directory cd to "benchmarks/", and configure the parameters in benchmark scripts

   For example, in run_rt.py, you can config the 'parallelMode': True if you are running a multi-core machine. You can also set 'rounds': 1 for testing, which can make the execution finish soon.

3. Run the benchmark scripts

     $ python run_rt.py
     $ python run_tp.py 
   

4. Check the evaluation results in "benchmarks/result/" directory. Note that the repository has maintained the results evaluated on WS-DREAM datasets, which are ready for immediate use.

Feedback

For bugs and feedback, please post to our issue page. For any other enquires, please drop an email to our team (wsdream.maillist@gmail.com).

License

The MIT License (MIT)

Copyright © 2017, WS-DREAM, CUHK