Execution Management and Efficient Resource Provisioning for Flood Decision Support

Abstract

We present a resource provisioning and execution management solution for a flood decision support system. The system, developed within the ISMOP project, features an urgent computing scenario in which flood threat assessment for large sections of levees is requested within a specified deadline. Unlike typical decision support systems which utilize heavyweight simulations in order to predict the possible course of an emergency, in ISMOP we employ an alternative approach based on the ‘scenario identification’ method. We show that this approach is a particularly good fit for the resource provisioning model of IaaS Clouds. We describe the architecture of the ISMOP decision support system, focusing on the urgent computing scenario and its formal resource provisioning model. Preliminary results of experiments performed in order to calibrate and validate the model indicate that the model fits experimental data.