Dynamic Performance Profiling of Cloud Caches
- Submitting institution
-
Royal Holloway and Bedford New College
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 28992772
- Type
- E - Conference contribution
- DOI
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10.1145/2670979.2671007
- Title of conference / published proceedings
- 5th ACM Symposium on Cloud Computing (SOCC'14)
- First page
- 1
- Volume
- -
- Issue
- -
- ISSN
- -
- Open access status
- -
- Month of publication
- November
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
-
- 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
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3
- Research group(s)
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-
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper proposes two novel and practical techniques for estimating the utility of a network cache as a function of its size. The approximation error is bounded both theoretically and confirmed through extensive empirical studies using the real life application cache workloads. The results have inspired different groups e.g. at MIT, Stanford and Carnegie Mellon, that work in the management of shared space resources within the clouds and virtual machine hypervisors e.g. Cidon et al (USENIX'16) and Berger et al NSDI'17. ACM SOCC is a leading conference in cloud computing.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -