System identification: theory for the user
System identification: theory for the user
Dynamic structure in software architectures
SIGSOFT '96 Proceedings of the 4th ACM SIGSOFT symposium on Foundations of software engineering
Modern Control Engineering
Control Theory-Based Foundations of Self-Controlling Software
IEEE Intelligent Systems
A Feedback Control Approach for Guaranteeing Relative Delays in Web Servers
RTAS '01 Proceedings of the Seventh Real-Time Technology and Applications Symposium (RTAS '01)
SWiFT: A Feedback Control and Dynamic Reconfiguration Toolkit
SWiFT: A Feedback Control and Dynamic Reconfiguration Toolkit
Feedback Control of Computing Systems
Feedback Control of Computing Systems
Computer
Managing Web server performance with AutoTune agents
IBM Systems Journal
Self-Managing Systems: A Control Theory Foundation
LCN '04 Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks
Self-Optimization in Computer Systems via On-Line Control: Application to Power Management
ICAC '04 Proceedings of the First International Conference on Autonomic Computing
Triage: Performance differentiation for storage systems using adaptive control
ACM Transactions on Storage (TOS)
A real-time adaptive control of autonomic computing environments
CASCON '07 Proceedings of the 2007 conference of the center for advanced studies on Collaborative research
From goals to components: a combined approach to self-management
Proceedings of the 2008 international workshop on Software engineering for adaptive and self-managing systems
Rainbow: cost-effective software architecture-based self-adaptation
Rainbow: cost-effective software architecture-based self-adaptation
ICAC '06 Proceedings of the 2006 IEEE International Conference on Autonomic Computing
What does control theory bring to systems research?
ACM SIGOPS Operating Systems Review
Self-adaptive software: Landscape and research challenges
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Model Predictive Control System Design and Implementation Using MATLAB
Model Predictive Control System Design and Implementation Using MATLAB
From Data Center Resource Allocation to Control Theory and Back
CLOUD '10 Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing
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Due to the increasing complexity of software systems and the dynamic unpredictable environments they operate in, methodologies to incorporate self-adaptation into these systems have been investigated in recent years. The feedback control loop has been one of the key concepts used in building self-adaptive software systems to manage their performance among other quality aspects. In order to design an effective feedback control loop for a software system, modeling the behavior of the software system with sufficient accuracy is paramount. In general, there are many environmental conditions and system states that impact on the performance of a software system. As a consequence, it is impractical to characterize the diverse behavior of such a software system using a single system model. To represent such highly nonlinear behavior and to provide effective runtime control, the design, integration and self-management (automatic switching) of multiple system models and controllers are required. In this paper, we investigate a control engineering approach, called Multi-Model Switching and Tuning (MMST) adaptive control, to assess its effectiveness for the adaptive performance management of software systems. We have conducted a range of experiments with two of the most promising MMST adaptive control schemes under different operating conditions of a representative software system. The experiment results have shown that the MMST control schemes are superior in managing the performance of the software system, compared with a number of other control schemes based on a single model. We have also investigated the impact of the configuration parameters for the MMST schemes to provide design guidance. A library of MMST schemes has been implemented to aid the software engineer in developing MMST-based self-managing control schemes for software systems.