Using clouds to scale grid resources: An economic model
Future Generation Computer Systems
Caching VM instances for fast VM provisioning: a comparative evaluation
Euro-Par'12 Proceedings of the 18th international conference on Parallel Processing
An extreme automation framework for scaling cloud applications
IBM Journal of Research and Development
A Value Based Dynamic Resource Provisioning Model in Cloud
International Journal of Cloud Applications and Computing
Solidifying the foundations of the cloud for the next generation Software Engineering
Journal of Systems and Software
A Value Based Dynamic Resource Provisioning Model in Cloud
International Journal of Cloud Applications and Computing
Scheduling highly available applications on cloud environments
Future Generation Computer Systems
A cost-aware auto-scaling approach using the workload prediction in service clouds
Information Systems Frontiers
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The Cloud phenomenon brings along the cost-saving benefit of dynamic scaling. As a result, the question of efficient resource scaling arises. Prediction is necessary as the virtual resources that Cloud computing uses have a setup time that is not negligible. We propose an approach to the problem of workload prediction based on identifying similar past occurrences of the current short-term workload history. We present in detail the Cloud client resource auto-scaling algorithm that uses the above approach to help when scaling decisions are made, as well as experimental results by using real-world traces from Cloud and Grid platforms. We also present an overall evaluation of this approach, its potential and usefulness for enabling efficient auto-scaling of Cloud user resources.