Performance Anomaly Detection
Performance Anomaly Detection is a computational method that identifies deviations in system behavior indicative of performance degradation in multi-tenant environments by distinguishing abnormal resource utilization patterns from normal operational baselines.
166
Publications
8.1K
Citations
583
Authors
216
Institutions
Publications per year
2017–2026
64
166
Performance anomaly of 802.11b
Martin Heusse, Franck Rousseau, Gilles Berger-Sabbatel et al. · 2003 · 1.2K citations
Characterization of storage workload traces from production Windows Servers
Swaroop Kavalanekar, Bruce Worthington, Qi Zhang et al. · 2008 · 259 citations
Statistical techniques for online anomaly detection in data centers
Chengwei Wang, Krishnamurthy Viswanathan, Choudur Lakshminarayan et al. · 2011 · 178 citations
PREPARE: Predictive Performance Anomaly Prevention for Virtualized Cloud Systems
Yongmin Tan, Hiep Nguyen, Zhiming Shen et al. · 2012 · 160 citations
1–5 of 166
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216
Microsoft (United States)
Redmond, United States
8 h-index
23 publications
5.3K citations

University of Coimbra
Coimbra, Portugal
6 h-index
6 publications
136 citations
Tsinghua University
Beijing, China
6 h-index
29 publications
1.6K citations
Queen's University
Kingston, Canada
5 h-index
12 publications
532 citations
Hewlett-Packard (United States)
Palo Alto, United States
5 h-index
17 publications
1.3K citations
North Carolina State University
Raleigh, United States
5 h-index
17 publications
1.3K citations

Polytechnic Institute of Porto
Porto, Portugal
5 h-index
5 publications
113 citations
IBM (United States)
Armonk, United States
4 h-index
9 publications
495 citations
1–8 of 216
TPDS · 3 publications · 144 citations
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3 publications · 49 citations
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TNSM · 3 publications · 94 citations
3
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TKDE · 2 publications · 46 citations
2
h-index
TON · 2 publications · 88 citations
2
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