LUCS Evaluation
We propose the mathematical model for scalable and accurate prediction of availability of atomic web services. The model we propose, LUCS, estimates the service availability for an ongoing request by considering its similarity to prior requests according to the following dimensions: the user’s and service’s geographic location, the service load, and the service’s computational requirements.
In order to evaluate our model, we conducted experiments on services deployed in different regions of the Amazon EC2 cloud.
We provide all relevant data and code of our evaluation on this website:
- We provide the zip file containing MS Excell files with the input data that was collected from distributed agents on the Amazon Cloud.
Input_Data_Excell - Also, we provide the implementation of services that were used in our experiments.
LUCS_WS_Services_Implementation - We provide the LUCS evaluation source code, implemented in Microsoft Visual Studio 2010. in C#.
LUCS_Evaluation_Source_Code - We provide the release of the application for the evaluation of LUCS
(Note: The zip contains to folders input and output. The input folder contains series of simple *.txt files with the same data as the one provided in (1). The input folder should be put in the same directory along with the release application. The results of the evaluation are written in the files in the output folder. However, the output folder is not necessarily for the release application to run, but the input folder is).
LUCS_Evaluation_App - We provide Wolfram math files containing containing the output data used for rendering the graphs provided in the manuscript.
LUCS_Evaluation_Output_Wolfram
Data Usage and Acknowledgement
The data provided in (1) was collected in series of experiments conducted on the Amazon EC2 cloud. If you are using this data in a paper, please send an e-mail with the paper reference to the authors and we will add it to this page.
If you use these data in your work, please acknowledge the authors.
@article{6409351,
author={Silic, M. and Delac, G. and Krka, I. and Srbljic, S.},
journal={Services Computing, IEEE Transactions on},
title={Scalable and Accurate Prediction of Availability of Atomic Web Services},
year={2013},
volume={PP},
number={99},
pages={1-1},
keywords={Web services;prediction model;service availability},
doi={10.1109/TSC.2013.3},
ISSN={1939-1374},}
