The SR-tree: an index structure for high-dimensional nearest neighbor queries
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
LOF: identifying density-based local outliers
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
A methodology for workload characterization of E-commerce sites
Proceedings of the 1st ACM conference on Electronic commerce
Characterizing the scalability of a large web-based shopping system
ACM Transactions on Internet Technology (TOIT)
TPC-W: A Benchmark for E-Commerce
IEEE Internet Computing
ECOOP '01 Proceedings of the 15th European Conference on Object-Oriented Programming
DSN '02 Proceedings of the 2002 International Conference on Dependable Systems and Networks
Proactive Detection of Software Aging Mechanisms in Performance Critical Computers
SEW '02 Proceedings of the 27th Annual NASA Goddard Software Engineering Workshop (SEW-27'02)
A Methodology for Detection and Estimation of Software Aging
ISSRE '98 Proceedings of the The Ninth International Symposium on Software Reliability Engineering
A Measurement-Based Model for Estimation of Resource Exhaustion in Operational Software Systems
ISSRE '99 Proceedings of the 10th International Symposium on Software Reliability Engineering
An Approach for Estimation of Software Aging in a Web Server
ISESE '02 Proceedings of the 2002 International Symposium on Empirical Software Engineering
Software Rejuvenation: Analysis, Module and Applications
FTCS '95 Proceedings of the Twenty-Fifth International Symposium on Fault-Tolerant Computing
An analytical model for multi-tier internet services and its applications
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Ensembles of Models for Automated Diagnosis of System Performance Problems
DSN '05 Proceedings of the 2005 International Conference on Dependable Systems and Networks
Failure detection and localization in component based systems by online tracking
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Tracking Probabilistic Correlation of Monitoring Data for Fault Detection in Complex Systems
DSN '06 Proceedings of the International Conference on Dependable Systems and Networks
Modeling and Tracking of Transaction Flow Dynamics for Fault Detection in Complex Systems
IEEE Transactions on Dependable and Secure Computing
Path-based faliure and evolution management
NSDI'04 Proceedings of the 1st conference on Symposium on Networked Systems Design and Implementation - Volume 1
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Using magpie for request extraction and workload modelling
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Why do internet services fail, and what can be done about it?
USITS'03 Proceedings of the 4th conference on USENIX Symposium on Internet Technologies and Systems - Volume 4
Efficient and Scalable Algorithms for Inferring Likely Invariants in Distributed Systems
IEEE Transactions on Knowledge and Data Engineering
A comparative study of pairwise regression techniques for problem determination
CASCON '07 Proceedings of the 2007 conference of the center for advanced studies on Collaborative research
Semantic-Driven Model Composition for Accurate Anomaly Diagnosis
ICAC '08 Proceedings of the 2008 International Conference on Autonomic Computing
Discovering Likely Invariants of Distributed Transaction Systems for Autonomic System Management
ICAC '06 Proceedings of the 2006 IEEE International Conference on Autonomic Computing
ACM Computing Surveys (CSUR)
System monitoring with metric-correlation models: problems and solutions
ICAC '09 Proceedings of the 6th international conference on Autonomic computing
Automated anomaly detection and performance modeling of enterprise applications
ACM Transactions on Computer Systems (TOCS)
Detecting large-scale system problems by mining console logs
Proceedings of the ACM SIGOPS 22nd symposium on Operating systems principles
Model-Driven System Capacity Planning under Workload Burstiness
IEEE Transactions on Computers
On the use of computational geometry to detect software faults at runtime
Proceedings of the 7th international conference on Autonomic computing
PeerWatch: a fault detection and diagnosis tool for virtualized consolidation systems
Proceedings of the 7th international conference on Autonomic computing
Detection of Performance Anomalies in Web-Based Applications
NCA '10 Proceedings of the 2010 Ninth IEEE International Symposium on Network Computing and Applications
Invariants Based Failure Diagnosis in Distributed Computing Systems
SRDS '10 Proceedings of the 2010 29th IEEE Symposium on Reliable Distributed Systems
Root-cause analysis of performance anomalies in web-based applications
Proceedings of the 2011 ACM Symposium on Applied Computing
IEEE Transactions on Dependable and Secure Computing
Bench4Q: A QoS-Oriented E-Commerce Benchmark
COMPSAC '11 Proceedings of the 2011 IEEE 35th Annual Computer Software and Applications Conference
Detecting application-level failures in component-based Internet services
IEEE Transactions on Neural Networks
PREPARE: Predictive Performance Anomaly Prevention for Virtualized Cloud Systems
ICDCS '12 Proceedings of the 2012 IEEE 32nd International Conference on Distributed Computing Systems
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The failure of Web applications often affects a large population of customers, and leads to severe economic loss. Anomaly detection is essential for improving the reliability of Web applications. Current approaches model correlations among metrics, and detect anomalies when the correlations are broken. However, dynamic workloads cause the metric correlations to change over time. Moreover, modeling various metric correlations are difficult in complex Web applications. This paper addresses these problems and proposes an online anomaly detection approach for Web applications. We present an incremental clustering algorithm for training workload patterns online, and employ the local outlier factor (LOF) in the recognized workload pattern to detect anomalies. In addition, we locate the anomalous metrics with the Student's t-test method. We evaluated our approach on a testbed running the TPC-W industry-standard benchmark. The experimental results show that our approach is able to (1) capture workload fluctuations accurately, (2) detect typical faults effectively and (3) has advantages over two contemporary ones in accuracy.