Abstract: This paper is the preface to the Third Workshop on Urgent Computing. The Urgent Computing workshops have been traditionally embedded in frame of International Conference of Computational Science (ICCS) since 2012. They are aimed to develop a dialogue on the present and future of research and applications associated with the large-scale computations for decision support in critical situations. The key workshop topics in 2014 are: methods and principles of urgent computing, middleware, platforms and infrastructures, simulation-based decision support for complex systems control, interactive visualization and virtual reality for decision support in emergency situations, domain-area applications to emergency situations, including natural and man-made disasters, e.g. transportation problems, epidemics, criminal acts, etc.

Abstract: This article discusses aspects of implementation of a massive personal decision support mobile service for evacuation process in extreme situations, based on second-generation cloud computation platform CLAVIRE and a virtual society model. The virtual society model was constructed using an agent-based approach. To increase credibility the individual motivation methods (personal decision support and user training) were used.

Abstract: One of the most important issues in Decision Support Systems (DSS) technology is in ensuring their effectiveness and efficiency for future implementations and use. DSS is prominent tool in disaster information system, which allows the authority to provide life safety information directly to the mobile devices of anyone physically located in the evacuation area. After that a personal DSS guides users to a safe point. Due to the large uncertainty in initial conditions and assumptions on underlying process such DSS is extremely hard for implementation and evaluation, particularly in real environment. We propose a simulation methodology for the evaluation of in-vehicle DSS for emergency evacuation based on transport system and human decision-making modeling.

Abstract: Saint-Petersburg Flood Warning System (FWS) is a life-critical system that requires permanent maintenance and development. Tasks that arise during these processes could be much more resource-intensive than an operational loop of the system and may involve complex problems for research. Thereby it is essential to have a special software tool to handle a collection of different models, data sources and auxiliary software that they could be combined in different ways according to a particular research problem to be solved. This paper aims to share the idea of Saint-Petersburg FWS evolution with help of problem-solving environment based on the cloud platform CLAVIRE.