Published June 5, 2017 | Version v1
Dataset Open

Accelerating Performance Inference over Closed Systems by Asymptotic Methods

Authors/Creators

  • 1. Imperial College London

Description

This archive includes the research data associated to the paper:

Giuliano Casale. Accelerating Performance Inference over Closed Systems by Asymptotic Methods. Proc. ACM Meas. Anal. Comput. Syst., 1(1), 2017. The paper is accepted for presentation at ACM SIGMETRICS 2017.

The research data requires MATLAB 2015a or later. Four datasets are included, each corresponding to a section of the paper:
- sec5.3.1: Small and medium models without infinite server nodes (Section 5.3.1)
- sec5.3.2: Large models without infinite server nodes (Section 5.3.2)
- sec5.3.3: Models with infinite server nodes (Section 5.3.3)
- sec5.4: Optimization programs (Section 5.4)

A description of each dataset is included in the README.TXT file inside each folder.

Files

INDEX.TXT

Files (59.2 MB)

Name Size Download all
md5:97824a186a408d1cfcede68c7c79c968
758 Bytes Preview Download
md5:f4214d52c018546cb629c2bed912cf9f
963.0 kB Preview Download
md5:632892bb271cb09f91e1dc5ba58d3b1d
3.6 MB Preview Download
md5:590896a2bdb4e29150401b0fdfc436bf
7.0 MB Preview Download
md5:4590728046c02fd93ca5547492539dbf
47.6 MB Preview Download

Additional details

Funding

European Commission
DICE - Developing Data-Intensive Cloud Applications with Iterative Quality Enhancements 644869