On the quantification of e-business capacity
Proceedings of the 3rd ACM conference on Electronic Commerce
Capacity Planning for Internet Services
Capacity Planning for Internet Services
On the Modeling of WWW Request Arrivals
ICPP '99 Proceedings of the 1999 International Workshops on Parallel Processing
Dynamic web log session identification with statistical language models
Journal of the American Society for Information Science and Technology - Special issue: Webometrics
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
Blind source separation of positive and partially correlated data
Signal Processing
Parameter inference of queueing models for IT systems using end-to-end measurements
Performance Evaluation
Capacity planning tools for web and grid environments
valuetools '06 Proceedings of the 1st international conference on Performance evaluation methodolgies and tools
Path-based faliure and evolution management
NSDI'04 Proceedings of the 1st conference on Symposium on Networked Systems Design and Implementation - Volume 1
Performance modeling and system management for multi-component online services
NSDI'05 Proceedings of the 2nd conference on Symposium on Networked Systems Design & Implementation - Volume 2
Using magpie for request extraction and workload modelling
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
A Regression-Based Analytic Model for Dynamic Resource Provisioning of Multi-Tier Applications
ICAC '07 Proceedings of the Fourth International Conference on Autonomic Computing
Exploiting nonstationarity for performance prediction
Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007
Performance impacts of autocorrelated flows in multi-tiered systems
Performance Evaluation
Workload Analysis and Demand Prediction of Enterprise Data Center Applications
IISWC '07 Proceedings of the 2007 IEEE 10th International Symposium on Workload Characterization
Estimating service resource consumption from response time measurements
Proceedings of the Fourth International ICST Conference on Performance Evaluation Methodologies and Tools
Autonomic mix-aware provisioning for non-stationary data center workloads
Proceedings of the 7th international conference on Autonomic computing
Tracking adaptive performance models using dynamic clustering of user classes
Proceedings of the 2nd ACM/SPEC International Conference on Performance engineering
Modellus: Automated modeling of complex internet data center applications
ACM Transactions on the Web (TWEB)
Systematic adoption of genetic programming for deriving software performance curves
ICPE '12 Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering
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Modeling system performance and workload characteristics has become essential for efficiently provisioning Internet services and for accurately predicting future resource requirements on anticipated workloads. The accuracy of these models benefits substantially by differentiating among categories of requests based on their resource usage characteristics. However, categorizing requests and their resource demands often requires significantly more monitoring infrastructure. In this paper, we describe a method to automatically differentiate and categorize requests without requiring sophisticated monitoring techniques. Using machine learning, our method requires only aggregate measures such as total number of requests and the total CPU and network demands, and does not assume prior knowledge of request categories or their individual resource demands. We explore the feasibility of our method on the .Net PetShop 4.0 benchmark application, and show that it works well while being lightweight, generic, and easily deployable.