@conference {jopera:2008:icac,
	title = {Automatic Configuration of an Autonomic Controller: An Experimental Study with Zero-Configuration Policies},
	booktitle = {5th International Conference on Autonomic Computing (ICAC 2008)},
	year = {2008},
	month = {June},
	pages = {67-76},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Chicago, IL, USA},
	abstract = {Autonomic control managers can remove the need for manual system configuration in order to achieve good performance and efficient resource utilization. However, simple controllers based on reconfiguration actions tied to thresholds, or {\textquoteright}if-then{\textquoteright} rules, themselves need to be configured and tuned in order to adapt the controller behavior to the expected workload characteristic. In this paper we present an experimental study of zero-configuration policies that can be automatically tuned based on analytical models of the system under control. In particular, we have designed and implemented a threshold-free self-configuration policy for a distributed workflow execution engine and compared it with a standard PID controller. The experimental results included in the paper show that using such a policy the controller can tune itself in addition to reconfiguring the distributed engine and the proposed policy out-performs simpler policies that require manual and error-prone tuning of their parameters.},
	keywords = {analytical models, automatic configuration, automatic control, autonomic controller, control system synthesis, distributed workflow execution engine, PID control, resource management, resource utilization, workload characteristic, zero-configuration policies},
	doi = {10.1109/ICAC.2008.29},
	author = {Thomas Heinis and Cesare Pautasso}
}
@conference {jopera:2005:icac,
	title = {Design and Evaluation of an Autonomic Workflow Engine},
	booktitle = {2nd International Conference on Autonomic Computing (ICAC-05)},
	year = {2005},
	month = {June},
	pages = {27 - 38},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Seattle, Washington},
	abstract = {In this paper we present the design and evaluate the performance of an autonomic workflow execution engine. Although there exist many distributed workflow engines, in practice, it remains a difficult problem to deploy such systems in an optimal configuration. Furthermore, when facing an unpredictable workload with high variability, manual reconfiguration is not an option. Thanks to its autonomic controller, the engine features self-configuration, self-tuning and self-healing properties. The engine runs on a cluster of computers using a tuple space to coordinate its various components. Its autonomic controller monitors its performance and responds to workload variations by altering the configuration. In case failures occur, the controller can recover the workflow execution state from persistent storage and migrate it to a different node of the cluster. Such interventions are carried out without any human supervision. As part of the results of our performance evaluation, we compare different autonomic control strategies and discuss how they can automatically tune the system},
	keywords = {automatic configuration, autonomic computing, JOpera, Web service composition},
	doi = {10.1109/ICAC.2005.21},
	author = {Thomas Heinis and Cesare Pautasso and Gustavo Alonso}
}
