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M. Maurer, I. Brandic, R. Sakellariou:
"Self-Adaptive and Resource-Efficient SLA Enactment for Cloud Computing Infrastructures";
Talk: IEEE 5th International Conference on Cloud Computing, CLOUD 2012, Honolulu, Hawaii, USA; 06-24-2012 - 06-29-2012; in: "Proceedings of the IEEE 5th International Conference on Cloud Computing, CLOUD 2012", R. Chang (ed.); IEEE Computer Society, (2012), ISBN: 978-0-7695-4755-8; 368 - 375.

Cloud providers aim at guaranteeing Service Level Agreements (SLAs) in a resource-efficient way. This, amongst others, means that resources of virtual (VMs) and physical machines (PMs) have to be autonomically allocated responding to external influences as workload or environmental changes. Thereby, workload volatility (WV) is one of the crucial factors that influence the quality of suggested allocations. In this paper we devise a novel approach for self-adaptive and resourceefficient decision-making considering the three conflicting goals of minimizing the number of SLA violations, maximizing resource utilization, and minimizing the number of necessary time- and energy-consuming reconfiguration actions. We propose self-adaptive rule-based knowledge management for autonomic
VM reconfiguration considering the rapidness of changes in the
workload, i.e., WV. We introduce a novel WV categorization and present cost and volatility based methods for self-tuning. We evaluate these methods by a large variety of synthetically
generated workloads, and by real-world measurements gathered
from an image rendering application and a scientific workflow
for RNA sequencing. Evaluation shows that in most cases the
self-adaptive approach outperforms the static approach.

Cloud Computing, Autonomic Computing, Self-Adaptation, Service Level Agreement, Rule-based System, Knowledge Management, Resource Management

http://dx.doi.org/10.1109/CLOUD.2012.55

Project Head Ivona Brandic:
Foundations of Self-governing ICT Infrastructures