Projects per year
Abstract
Cloud data centres are critical business infrastructures and the fastest growing service providers. Detecting
anomalies in Cloud data centre operation is vital. Given the vast complexity of the data centre system software
stack, applications and workloads, anomaly detection is a challenging endeavour. Current tools for detecting
anomalies often use machine learning techniques, application instance behaviours or system metrics distribu-
tion, which are complex to implement in Cloud computing environments as they require training, access to
application-level data and complex processing. This paper presents LADT, a lightweight anomaly detection
tool for Cloud data centres that uses rigorous correlation of system metrics, implemented by an efficient corre-
lation algorithm without need for training or complex infrastructure set up. LADT is based on the hypothesis
that, in an anomaly-free system, metrics from data centre host nodes and virtual machines (VMs) are strongly
correlated. An anomaly is detected whenever correlation drops below a threshold value. We demonstrate and
evaluate LADT using a Cloud environment, where it shows that the hosting node I/O operations per second
(IOPS) are strongly correlated with the aggregated virtual machine IOPS, but this correlation vanishes when
an application stresses the disk, indicating a node-level anomaly.
Original language | English |
---|---|
Title of host publication | Proceedings on 5th International Conference on Cloud Computing and Services Science (CLOSER 2015) |
Publisher | SciTePress |
Pages | 343-351 |
DOIs | |
Publication status | Published - 2015 |
Event | 5th International Conference on Cloud Computing and Services Science, CLOSER 2015 - Lisbon, Portugal Duration: 20 May 2015 → 22 May 2015 |
Conference
Conference | 5th International Conference on Cloud Computing and Services Science, CLOSER 2015 |
---|---|
Country/Territory | Portugal |
City | Lisbon |
Period | 20/05/2015 → 22/05/2015 |
Bibliographical note
Best Paper Award NomineeKeywords
- Anomaly detection
- Cloud computing
- Data centres
- Monitoring
- Correlation
Fingerprint
Dive into the research topics of 'A Lightweight Tool for Anomaly Detection in Cloud Data Centres'. Together they form a unique fingerprint.Projects
- 1 Finished
-
R6405CSC: CACTOS: Context-Aware Cloud Topology Optimisation and Simulation
Nikolopoulos, D. (PI), Kilpatrick, P. (CoI) & McCollum, B. (CoI)
01/08/2013 → 30/09/2016
Project: Research