Alexander V. Boukhanovsky

CLAVIRE: e-Science infrastructure for data-driven computing

Abstract The paper introduces CLAVIRE (CLoud Applications VIRtual Environment) platform. Architecture of the platform is shown with a focus on the abstraction which enables the integration of the distributed computational resources, data sources and the software. Coupled domain-specific languages EasyFlow and EasyPackage for unified workflow design are represented. Five classes of users’ interfaces are proposed as a basis for human–computer interaction support in CLAIRE. Interactive workflow model is implemented as a prospective approach for data-driven composite applications.

Simulation-based collaborative decision support for surge floods prevention in St. Petersburg

Abstract The paper aims to implement a simulation-based collaborative decision support approach for flood control management in application to St. Petersburg surge floods, which are prevented by a complex of dams with several large openings. Despite the evolution of the numerical hydrodynamic models, hardware performance and computer technologies the accurate forecasting of storm surges and decision support for gates maneuvering is still an important issue. The prospective architecture and principal solutions of Flood Warning System with the emphasis on the simulation-based approach and collaborative decision support system on the basis of e-Science platform CLAVIRE are considered.

Distributed simulation of city inundation by coupled surface and subsurface porous flow for urban flood decision support system

We present a decision support system for flood early warning and disaster management. It includes the models for data- driven meteorological predictions, for simulation of atmospheric pressure, wind, long sea waves and seiches; a module for optimization of flood barrier gates operation; models for stability assessment of levees and embankments, for simulation of city inundation dynamics and citizens evacuation scenarios. The novelty of this paper is a coupled distributed simulation of surface and subsurface flows that can predict inundation of low-lying inland zones far away from the edge of the flooded area, as observed in St. Petersburg city during the floods. All the models are wrapped as software services in the CLAVIRE platform for urgent computing, which provides workflow management and resource orchestration.

Russian-Dutch double-degree Master’s programme in computational science in the age of global education

Abstract We present a new double-degree graduate (Master’s) programme developed together by the ITMO University, Russia and University of Amsterdam, The Netherlands. First, we look into the global aspects of integration of different educational systems and list some funding opportunities. Then, we describe our double-degree program curriculum, suggest the timeline of enrollment and studies, and give some examples of student research topics. Finally, we discuss the issues of joint programs with Russia and suggest possible solutions, analyze the results of the first three student intakes and reflect on the lessons learnt, and share our thoughts and experiences that could be of interest to the international community expanding the educational markets to the vast countries like Russia, China or India. The paper is written for education professionals and contains useful information for potential students. This is an extended version of a conference paper ( http://dx.doi.org/10.1016/j.procs.2014.05.130 ) invited to this special issue of the Journal of Computational Science.

A Generic Architecture for a Social Network Monitoring and Analysis System

This paper describes the architecture and a partial implementation of a system designed for the monitoring and analysis of communities at social media sites. The main contribution of the paper is a novel system architecture that facilitates long-term monitoring of diverse social networks existing and emerging at various social media sites. It consists of three main modules, the crawler, the repository and the analyzer. The first module can be adapted to crawl different sites based on ontology describing the structure of the site. The repository stores the crawled and analyzed persistent data using efficient data structures. It can be implemented using special purpose graph databases and/or object-relational database. The analyzer hosts modules that can be used for various graph and multimedia contents analysis tasks. The results can be again stored to the repository, and so on. All modules can be run concurrently.

Urgent Computing for Operational Storm Surge Forecasting in Saint-Petersburg

Abstract The accurate forecasting of storm surges and decision support for gates maneuvering is an important issue in Saint-Petersburg. The evolution of the numerical hydrodynamic models, hardware performance and computer technologies allow to make Flood Warning System (FWS) in Saint-Petersburg more reliable and appropriate to the real needs. This article describes the key solutions of the development and the present operational set-up of FWS with emphasis on computational issues and decision support on the basis of urgent computing paradigm. It includes a brief description data-assimilation techniques, such as Kalman filtering, the probabilistic real-data forecasting model, forecast quality control, distributed computing of different scenarios and decision support for gates maneuvering.

Virtual Simulation Objects concept as a framework for system-level simulation

This paper presents Virtual Simulation Objects (VSO) concept which forms theoretical basis for building tools and framework that is developed for system-level simulations using existing software modules available within cyber-infrastructure. Presented concept is implemented by the software tool for building composite solutions using VSO-based GUI and running them using CLAVIRE simulation environment.

Individual Decision Making Can Drive Epidemics: A Fuzzy Cognitive Map Study

Existing studies on the propagation of infectious diseases have not sufficiently considered the uncertainties that are related to individual behavior and its influence on individual decision making to prevent infections, even though it is well known that changes in behavior can lead to variations in the macrodynamics of the spread of infectious diseases. These influencing factors can be categorized into emotion-related and cognition-related components. We present a fuzzy cognitive map (FCM) denotative model to describe how the factors of individual emotions and cognition influence each other. We adjust the weight matrix of causal relationships between these factors by using a so-called nonlinear Hebbian learning method. Based on this FCM model, we can implement individual decision rules against possible infections for disease propagation studies. We take the simulation of influenza A [H1N1] spreading on a campus as an example. We find that individual decision making against infections (frequent washing, respirator usage, and crowd contact avoidance) can significantly decrease the at-peak number of infected patients, even when common policies, such as isolation and vaccination, are not deployed.

Knowledge-Based Resource Management for Distributed Problem Solving

Knowledge-based approach for composite high-performance application building and execution is proposed as a solution to solving complex computational-intensive scientific tasks using set of existing software packages. The approach is based on semantic description of existing software, used within composite application. It allows building applications according to user quality requirements and domain-specific task description. CLAVIRE platform is described as an example of successful implementation of proposed approach’s basic principles. Exploration of described software solution performance characteristics is presented.

Interactive Workflow-based Infrastructure for Urgent Computing

Abstract Workflow became a mainstream formalism for complex scientific problems’ representation and is applied to different domains. In this paper we propose and analyze the interactive workflow model as the base for urgent computing (UC) infrastructures. Majority of research works in the area of urgent computing is focused on the deadline-driven scheduling issues for the existing high performance computing. This work tries to look at the problem of building a workflow-driven UC infrastructure from another side and to take into account the interactive nature of decision support. Workflow formalism is taken as the base for investigation. After analyzing the peculiarities of workflow-based UC infrastructure we propose an extended interactive workflow model. This model unifies the interactive capabilities of workflows and allows interactive systems to be described by consolidation of heterogeneous resources: high performance computing, users, software, external devices and data sources. This approach is represented on the crowd management application and is partially shown in the implemented prototype.