Agile dynamic provisioning of multi-tier Internet applications
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Automated control in cloud computing: challenges and opportunities
ACDC '09 Proceedings of the 1st workshop on Automated control for datacenters and clouds
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Resource pool management: Reactive versus proactive or let's be friends
Computer Networks: The International Journal of Computer and Telecommunications Networking
CloudCmp: comparing public cloud providers
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
Engineering autonomic controllers for virtualized web applications
ICWE'10 Proceedings of the 10th international conference on Web engineering
Adaptive resource provisioning for read intensive multi-tier applications in the cloud
Future Generation Computer Systems
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Elasticity is a key characteristic of cloud platforms enabling resource to be acquired on-demand in response to time-varying workloads. We introduce a new elasticity management framework that takes as input commonly used reactive rule-based scaling strategies but offers in return proactive auto-scaling. The elasticity framework combines reactive and predictive auto-scaling techniques, and we discuss the specification and performance of these individual components. We present a case study, based on real datasets, to demonstrate that our framework is capable of making appropriate auto-scaling decisions that can improve resource utilization compared to that obtained from a purely reactive approach.