Dynamic Virtual Clusters in a Grid Site Manager
HPDC '03 Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing
Design and Evaluation of an Autonomic Workflow Engine
ICAC '05 Proceedings of the Second International Conference on Automatic Computing
Virtual workspaces: Achieving quality of service and quality of life in the Grid
Scientific Programming - Dynamic Grids and Worldwide Computing
Live migration of virtual machines
NSDI'05 Proceedings of the 2nd conference on Symposium on Networked Systems Design & Implementation - Volume 2
Usher: an extensible framework for managing custers of virtual machines
LISA'07 Proceedings of the 21st conference on Large Installation System Administration Conference
SnowFlock: rapid virtual machine cloning for cloud computing
Proceedings of the 4th ACM European conference on Computer systems
The impact of management operations on the virtualized datacenter
Proceedings of the 37th annual international symposium on Computer architecture
A Survey on Cloud Computing Elasticity
UCC '12 Proceedings of the 2012 IEEE/ACM Fifth International Conference on Utility and Cloud Computing
Monitoring-as-a-service in the cloud: spec phd award (invited abstract)
Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering
An extreme automation framework for scaling cloud applications
IBM Journal of Research and Development
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The increasing popularity of system virtualization in datacenters introduces the need for self-scaling of the management layer to cope with the increasing demands of the management workload. This paper studies the problem of self-scaling in datacenter management middleware, allowing the management capacity to scale with the management workload. We argue that self-scaling must be fast during workload bursts to avoid task completion delays, and self-scaling must minimize resource usage to avoid resource contention with applications. To address these two challenges, we propose the design of Tide, a self-scaling framework for virtualized datacenter management. A salient feature of Tide is its fast capacity-provisioning algorithm that supplies just-enough capacity for the management middleware. We evaluate the effectiveness of Tide with both synthetic and real world workloads. Our results show that the self-scaling capability in Tide can substantially improve the throughput of management tasks during management workload bursts while consuming a reasonable amount of resources.