Urgent Computing: Computations for Decision Support in Critical Situations (UC) Session 1

Time and Date: 14:10 - 15:50 on 11th June 2014

Room: Mossman

Chair: Alexander Boukhanovsky

429 High Performance Computations for Decision Support in Critical Situations: Introduction to the Third Workshop on Urgent Computing [abstract]
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.
Alexander Boukhanovsky, Marian Bubak
342 Personal decision support mobile service for extreme situations [abstract]
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.
Vladislav A. Karbovskii, Daniil V. Voloshin, Kseniia A. Puzyreva, Aleksandr S. Zagarskikh
357 Evaluation of in-vehicle decision support system for emergency evacuation [abstract]
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.
Sergei Ivanov, Konstantin Knyazkov
358 Problem solving environment for development and maintenance of St. Petersburg’s Flood Warning System [abstract]
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.
Sergey Kosukhin, Anna Kalyuzhnaya, Denis Nasonov

Urgent Computing: Computations for Decision Support in Critical Situations (UC) Session 2

Time and Date: 16:20 - 18:00 on 11th June 2014

Room: Mossman

Chair: Alexander Boukhanovsky

366 Hybrid scheduling algorithm in early warning [abstract]
Abstract: Investigations in development of efficient early warning systems (EWS) are essentially for prediction and warning of upcoming natural hazards. Besides providing of communication and computationally intensive infrastructure, the high resource reliability and hard deadline option are required for EWS scenarios processing in order to get guaranteed information in time-limited conditions. In this paper planning of EWS scenarios execution is investigated and the efficient hybrid algorithm for urgent workflows scheduling is developed based on traditional heuristic and meta-heuristic approaches within state-of-art cloud computing principles.
Denis Nasonov, Nikolay Butakov
400 On-board Decision Support System for Ship Flooding Emergency Response [abstract]
Abstract: The paper describes a real-time software system to support emergency planning decisions when ship flooding occurs. The events of grounding and collision are considered, where the risk of subsequent flooding of hull compartments is very high, and must be avoided or at least minimized. The system is based on a highly optimized algorithm that estimates, ahead in time, the progressive flooding of the compartments according to the current ship status and existent damages. Flooding times and stability parameters are measured, allowing for the crew to take the adequate measures, such as isolate or counter-flood compartments, before the flooding takes incontrollable proportions. The simulation is visualized in a Virtual Environment in real-time, which provides all the functionalities to evaluate the seriousness and consequences of the situation, as well as to test, monitor and carry out emergency actions. Being a complex physical phenomena that occurs in an equally complex structure such as a ship, the real-time flooding simulation combined with the Virtual Environment requires large computational power to ensure the reliability of the simulation results. Moreover, the distress normally experienced by the crew in such situations, and the urgent (and hopefully appropriate) required counter-measures, leave no room for inaccuracies or misinterpretations, caused by the lack of computational power, to become acceptable. For the events considered, the system is primarily used as a decision support tool to take urgent actions in order to avoid or at least minimize disastrous consequences such as oil spilling, sinking, or even loss of human lives.
Jose Varela, Jose Rodrigues, Carlos Guedes Soares