Capacity Planning for Web Services: metrics, models, and methods
Capacity Planning for Web Services: metrics, models, and methods
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
Dynamic Provisioning of Multi-tier Internet Applications
ICAC '05 Proceedings of the Second International Conference on Automatic Computing
Resource Allocation for Autonomic Data Centers using Analytic Performance Models
ICAC '05 Proceedings of the Second International Conference on Automatic Computing
Detecting performance anomalies in global applications
WORLDS'05 Proceedings of the 2nd conference on Real, Large Distributed Systems - Volume 2
A Regression-Based Analytic Model for Dynamic Resource Provisioning of Multi-Tier Applications
ICAC '07 Proceedings of the Fourth International Conference on Autonomic Computing
Appliance-Based Autonomic Provisioning Framework for Virtualized Outsourcing Data Center
ICAC '07 Proceedings of the Fourth International Conference on Autonomic Computing
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It is a challenge to quickly supply performance numbers online driving dynamic resource provisioning in shared centres in face of the complication of applications both in scale and architecture. In this paper, we provide a practical solution to the above problem by laying out a theoretical framework. In order to improve the representative characterization of workload, we classify the workload into classes and adopt the regression-based methodology to extract these parameters online. We constructed both effective open and closed queuing models to evaluate the correctness and the generality of our idea. In our experiments, we analyse the effectiveness of the regression method with different number of classes. The results for the performance evaluation in the open queuing network show that almost 100% tests show relative error less than 2%, so these performance indexes can be effectively used as the basis for autonomic resource provisioning.