An Overview of Common Benchmarks
Computer
How is the weather tomorrow?: towards a benchmark for the cloud
Proceedings of the Second International Workshop on Testing Database Systems
VM3: Measuring, modeling and managing VM shared resources
Computer Networks: The International Journal of Computer and Telecommunications Networking
Performance Measurements and Analysis of Network I/O Applications in Virtualized Cloud
CLOUD '10 Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing
CloudGenius: decision support for web server cloud migration
Proceedings of the 21st international conference on World Wide Web
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The growing number of Cloud Infrastructure-as-a-Service (IaaS) offerings today leave a wide range of choices when deploying an application in the Cloud. Self-configuring and -optimizing autonomic systems have to select an infrastructure which fits the performance preferences while simultaneously offering the optimal performance per price ratio. A task which is not trivial. Indicators provided by providers are often not coherent and not sufficient to predict the actual performance of a deployed application and, thus, raise the need for benchmarking the offered services. This implies, however, intensive effort to gather the needed metrics, growing with every additional provider taken into consideration. In this paper we present an approach based on the theory of optimal stopping that enables an automated search for an optimal infrastructure service regarding performance-per-price-ratio while reducing costs for benchmarking.