The Markov-modulated Poisson process (MMPP) cookbook
Performance Evaluation
An EM algorithm for estimation in Markov-modulated Poisson processes
Computational Statistics & Data Analysis
Capacity Planning for Web Services: metrics, models, and methods
Capacity Planning for Web Services: metrics, models, and methods
Modelling with Generalized Stochastic Petri Nets
Modelling with Generalized Stochastic Petri Nets
The Vision of Autonomic Computing
Computer
Performance Evaluation of Complex Systems: Techniques and Tools, Performance 2002, Tutorial Lectures
From UML activity diagrams to Stochastic Petri nets: application to software performance engineering
WOSP '04 Proceedings of the 4th international workshop on Software and performance
Managing server energy and operational costs in hosting centers
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Efficient phase-type fitting with aggregated traffic traces
Performance Evaluation
Adaptive overload control for busy internet servers
USITS'03 Proceedings of the 4th conference on USENIX Symposium on Internet Technologies and Systems - Volume 4
Self-Managed Systems: an Architectural Challenge
FOSE '07 2007 Future of Software Engineering
Open versus closed: a cautionary tale
NSDI'06 Proceedings of the 3rd conference on Networked Systems Design & Implementation - Volume 3
Agile dynamic provisioning of multi-tier Internet applications
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
A survey of autonomic computing—degrees, models, and applications
ACM Computing Surveys (CSUR)
Autonomic multi-agent management of power and performance in data centers
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems: industrial track
Software Engineering for Self-Adaptive Systems: A Research Roadmap
Software Engineering for Self-Adaptive Systems
Markovian arrival process parameter estimation with group data
IEEE/ACM Transactions on Networking (TON)
Faster Maximum Likelihood Estimation Algorithms for Markovian Arrival Processes
QEST '09 Proceedings of the 2009 Sixth International Conference on the Quantitative Evaluation of Systems
Performance aware open-world software in a 3-layer architecture
Proceedings of the first joint WOSP/SIPEW international conference on Performance engineering
Recipe for efficiency: principles of power-aware computing
Communications of the ACM
Power optimization for dynamic configuration in heterogeneous web server clusters
Journal of Systems and Software
Energy-efficient server clusters
PACS'02 Proceedings of the 2nd international conference on Power-aware computer systems
KPC-Toolbox: Best recipes for automatic trace fitting using Markovian Arrival Processes
Performance Evaluation
Mistral: Dynamically Managing Power, Performance, and Adaptation Cost in Cloud Infrastructures
ICDCS '10 Proceedings of the 2010 IEEE 30th International Conference on Distributed Computing Systems
Performance sensitive self-adaptive service-oriented software using hidden Markov models
Proceedings of the 2nd ACM/SPEC International Conference on Performance engineering
Model-based self-adaptive resource allocation in virtualized environments
Proceedings of the 6th International Symposium on Software Engineering for Adaptive and Self-Managing Systems
Enhancing a QoS-based self-adaptive framework with energy management capabilities
Proceedings of the joint ACM SIGSOFT conference -- QoSA and ACM SIGSOFT symposium -- ISARCS on Quality of software architectures -- QoSA and architecting critical systems -- ISARCS
Dealing with Burstiness in Multi-Tier Applications: Models and Their Parameterization
IEEE Transactions on Software Engineering
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Energy use is becoming a key design consideration in computing infrastructures and services. In this paper we focus on service-based applications and we propose an adaptation framework that can be used to reduce power consumption according to the observed workload. The adaptation guarantees a trade-off between energy consumption and system performance. The approach is based on the principle of proportional energy consumption obtained by scaling down energy for unused resources, considering both the number of servers switched on and their operating frequencies. Stochastic Petri nets are proposed for the modeling of the framework concerns, their analyses give results about the trade-offs. The application of the approach to a simple case study shows its usefulness and practical applicability. Finally, different types of workloads are analyzed with validation purposes.