Accelerating performance inference over closed systems by asymptotic methods
- Submitting institution
-
Imperial College of Science, Technology and Medicine
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2393
- Type
- E - Conference contribution
- DOI
-
10.1145/3084445
- Title of conference / published proceedings
- Proceedings of the ACM on Measurement and Analysis of Computing Systems
- First page
- 1
- Volume
- 1
- Issue
- 1
- ISSN
- 2476-1249
- Open access status
- Compliant
- Month of publication
- June
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
10.1145/3078505.3078514
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
0
- Research group(s)
-
-
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Determining the normalising constant of state probabilities in closed queueing networks is one of the oldest research problems in the field (Buzen, CACM'73, https://doi.org/10.1145/362342.362345 ). We determine the first general explicit solution and associated asymptotic approximations. An implementation of the method has been included in the JMVA tool (http://jmt.sourceforge.net/JMVA.html), part of our JMT suite, with 5000 downloads per year (https://sourceforge.net/projects/jmt/files/stats/). Best paper award at SIGMETRICS'17, acceptance rate 13%/203.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
