Autonomic power and performance management for computing systems
Cluster Computing
Adapting to Run-Time Changes in Policies Driving Autonomic Management
ICAS '08 Proceedings of the Fourth International Conference on Autonomic and Autonomous Systems
SLA e-Negotiations, Enforcement and Management in an Autonomic Environment
MACE '08 Proceedings of the 3rd IEEE international workshop on Modelling Autonomic Communications Environments
Knowledge representation concepts for automated SLA management
Decision Support Systems
ICAC '09 Proceedings of the 6th international conference on Autonomic computing
VCONF: a reinforcement learning approach to virtual machines auto-configuration
ICAC '09 Proceedings of the 6th international conference on Autonomic computing
Sandpiper: Black-box and gray-box resource management for virtual machines
Computer Networks: The International Journal of Computer and Telecommunications Networking
A dynamic optimization model for power and performance management of virtualized clusters
Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking
Efficient resource provisioning in compute clouds via VM multiplexing
Proceedings of the 7th international conference on Autonomic computing
Autonomic mix-aware provisioning for non-stationary data center workloads
Proceedings of the 7th international conference on Autonomic computing
CLOUD '10 Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing
Maximizing Cloud Providers' Revenues via Energy Aware Allocation Policies
CLOUD '10 Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing
From Data Center Resource Allocation to Control Theory and Back
CLOUD '10 Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing
The reservoir model and architecture for open federated cloud computing
IBM Journal of Research and Development
Optimizing bioinformatics workflows for data analysis using cloud management techniques
Proceedings of the 6th workshop on Workflows in support of large-scale science
Energy-efficient and SLA-aware management of IaaS clouds
Proceedings of the 3rd International Conference on Future Energy Systems: Where Energy, Computing and Communication Meet
Differential time-shared virtual machine multiplexing for handling QoS variation in clouds
Proceedings of the 1st ACM multimedia international workshop on Cloud-based multimedia applications and services for e-health
Adaptive resource configuration for Cloud infrastructure management
Future Generation Computer Systems
Energy efficient service delivery in clouds in compliance with the kyoto protocol
E2DC'12 Proceedings of the First international conference on Energy Efficient Data Centers
Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference
Managing and Optimizing Bioinformatics Workflows for Data Analysis in Clouds
Journal of Grid Computing
Developing resource consolidation frameworks for moldable virtual machines in clouds
Future Generation Computer Systems
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The emergence of Cloud Computing raises the question of dynamically allocating resources of physical (PM) and virtual machines (VM) in an on-demand and autonomic way. Yet, using Cloud Computing infrastructures efficiently requires fulfilling three partially contradicting goals: first, achieving low violation rates of Service Level Agreements (SLA) that define non-functional goals between the Cloud provider and the customer; second, achieving high resource utilization; and third achieving the first two issues by as few time- and energy consuming reallocation actions as possible. To achieve these goals we propose a novel approach with escalation levels to divide all possible actions into five levels. These levels range from changing the configuration of VMs over migrating them to other PMs to outsourcing applications to other Cloud providers. In this paper we focus on changing the resource configuration of VMs in terms of storage, memory, CPU power and bandwidth, and propose a knowledge management approach using rules with threat thresholds to tackle this problem. Simulation reveals major improvements as compared to recent related work considering SLA violations, resource utilization and action efficiency, as well as time performance.