Scheduling strategies for enabling meteorological simulation on hybrid clouds

The flexible and pay-as-you-go computing capabilities offered by Cloud infrastructures are very attractive for high-demanding e-Science applications like weather prediction simulators. For their ability to couple the scalability offered by public service provider with the greater control and customization provided by Private Clouds, Hybrid Clouds seem a particularly appealing solution to support meteorological researchers and weather departments in their every-day activity. Cloud Brokers interfacing customers with Cloud providers, may support scientists in the deployment and execution of demanding meteorological simulations, by hiding all the intricacies related to the management of powerful but often complex HPC systems. The paper presents a set of brokering strategies for Hybrid Clouds aimed at the execution of various instances of the weather prediction WRF model subject to different user requirements and computational conditions. A simulation-based analysis documents the performance of the different scheduling strategies at varying workloads and system configuration. © 2014 Elsevier B.V. All rights reserved.