DejaVu: accelerating resource allocation in virtualized environments
ASPLOS XVII Proceedings of the seventeenth international conference on Architectural Support for Programming Languages and Operating Systems
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
Towards non-intrusive elastic query processing in the cloud
Proceedings of the fourth international workshop on Cloud data management
A Survey on Cloud Computing Elasticity
UCC '12 Proceedings of the 2012 IEEE/ACM Fifth International Conference on Utility and Cloud Computing
A game theoretical method for auto-scaling of multi-tiers web applications in cloud
Proceedings of the Fourth Asia-Pacific Symposium on Internetware
An untold story of redundant clouds: making your service deployment truly reliable
Proceedings of the 9th Workshop on Hot Topics in Dependable Systems
Introducing service-level awareness in the cloud
Proceedings of the 4th annual Symposium on Cloud Computing
Scheduling jobs in the cloud using on-demand and reserved instances
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
Quasar: resource-efficient and QoS-aware cluster management
Proceedings of the 19th international conference on Architectural support for programming languages and operating systems
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In this paper we present Kingfisher, a {\em cost-aware} system that provides efficient support for elasticity in the cloud by (i) leveraging multiple mechanisms to reduce the time to transition to new configurations, and (ii) optimizing the selection of a virtual server configuration that minimizes the cost. We have implemented a prototype of Kingfisher and have evaluated its efficacy on a laboratory cloud platform. Our experiments with varying application workloads demonstrate that Kingfisher is able to (i) decrease the cost of virtual server resources by as much as $24\%$ compared to the current cost-unaware approach, (ii) reduce by an order of magnitude the time to transition to a new configuration through multiple elasticity mechanisms in the cloud, and (iii), illustrate the opportunity for design alternatives which trade-off the cost of server resources with the time required to scale the application.