Automatically characterizing large scale program behavior
Proceedings of the 10th international conference on Architectural support for programming languages and operating systems
Xen and the art of virtualization
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Maestro-VC: A Paravirtualized Execution Environment for Secure On-Demand Cluster Computing
CCGRID '06 Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid
Virtual workspaces: Achieving quality of service and quality of life in the Grid
Scientific Programming - Dynamic Grids and Worldwide Computing
Applying a Dynamic Data Driven Genetic Algorithm to Improve Forest Fire Spread Prediction
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part III
From virtualized resources to virtual computing grids: the In-VIGO system
Future Generation Computer Systems - Special section: Complex problem-solving environments for grid computing
Virtual workspaces in the grid
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
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Virtualization technologies provide flexible execution environments that could bring important benefits for computational problems with strong deadlines. Large Grid infrastructures are becoming available nowadays and they could be a suitable environment to run such on-demand computations that might be used in decision-making processes. For these computation, we encounter the need to deliver as much resources as possible at particular times. These resources may be provided by different institutions belonging to a grid infrastructure but there are two important issues that must be satisfied. Firstly, all resources must be correctly configured and all the components needed by the application must be properly installed. If there is something small missing that is required then applications will fail. Secondly, the execution of urgent applications must be made quickly in order to produce useful results in time. If applications must wait in a queue, results might be useless because they are obtained too late. To address these issues, we describe a job management service, based on virtualization techniques, that avoids configuration problems and increases the number of available resources to run applications with critical deadlines. We describe the main components of our service that can be used on top of common batch queue systems and we show some experimental results that prove the benefits of applying time-sharing techniques on the virtual machines to increase the performance of urgent computations.