Quantitative system performance: computer system analysis using queueing network models
Quantitative system performance: computer system analysis using queueing network models
Capacity planning for Web performance: metrics, models, and methods
Capacity planning for Web performance: metrics, models, and methods
Multiclass queueing networks with population constrainted subnetworks
SIGMETRICS '85 Proceedings of the 1985 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Mean-Value Analysis of Closed Multichain Queuing Networks
Journal of the ACM (JACM)
Managing energy and server resources in hosting centers
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
IEEE Transactions on Software Engineering
Efficient approximation for models of multiprogramming with shared domains
SIGMETRICS '84 Proceedings of the 1984 ACM SIGMETRICS conference on Measurement and modeling of computer systems
QoS-Aware Middleware for Web Services Composition
IEEE Transactions on Software Engineering
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
Queue - Multiprocessors
Joint optimization of hardware and network systems
Journal of Parallel and Distributed Computing
Exploring performance trade-offs of a JPEG decoder using the deepcompass framework
WOSP '07 Proceedings of the 6th international workshop on Software and performance
Performance Modeling and Evaluation of Distributed Component-Based Systems Using Queueing Petri Nets
IEEE Transactions on Software Engineering
Power provisioning for a warehouse-sized computer
Proceedings of the 34th annual international symposium on Computer architecture
Multiobjective Optimization of SLA-Aware Service Composition
SERVICES '08 Proceedings of the 2008 IEEE Congress on Services - Part I
Approximate Solution of Multiclass Queuing Networks with Region Constraints
MASCOTS '07 Proceedings of the 2007 15th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems
Enhanced Modeling and Solution of Layered Queueing Networks
IEEE Transactions on Software Engineering
JMT: performance engineering tools for system modeling
ACM SIGMETRICS Performance Evaluation Review
ICAC '09 Proceedings of the 6th international conference on Autonomic computing
The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines
The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines
SAP Performance Optimization Guide
SAP Performance Optimization Guide
Managing on-demand business applications with hierarchical service level agreements
FIS'10 Proceedings of the Third future internet conference on Future internet
Feedback-based optimization of a private cloud
Future Generation Computer Systems
Towards software performance engineering for multicore and manycore systems
ACM SIGMETRICS Performance Evaluation Review
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We propose a model-based methodology to size and plan enterprise applications subject to Service Level Agreements (SLAs). Our approach is illustrated using a real-world Enterprise Resource Planning (ERP) application, namely SAP ERP. Firstly, we develop a closed queueing network model with finite capacity regions describing the SAP ERP application performance and show that this model is effective and robust in capturing measured response times and utilizations. Secondly, we propose an analytical cost model that jointly accounts for fixed hardware costs and dynamic operational costs related to power consumption. Based on the developed performance and cost models, we propose to use multi-objective optimization to find the Pareto-optimal solutions that describe the best trade-off solutions between conflicting performance and cost-saving goals. Experimental validation demonstrates the accuracy of the proposed models and shows that the attained Pareto-optimal solutions can be efficiently used by service providers for SLA-driven planning decisions, thus making a strong case in favor of the applicability of our methodology for deployment decisions subject to different SLA requirements.