DCSIMULTECH 2014 Abstracts


Paper Nr: 2
Title:

GIS-based Backcasting - A Method for Parameterisation of Sustainable Spatial Planning and Resource Management

Authors:

Eva Haslauer, Thomas Blaschke and Markus Biberacher

Abstract: Backcasting, if used as a decision support and planning method, starts from a desired future state or vision and simulates backwards until present time. During the model run, which goes backwards in time, development paths are created. They expose which steps have to be taken in future to reach the desired state. Besides, milestone scenarios are created as outputs that represent interim goals. The paper at hand proposes an automated, GISbased backcasting model, since backcasting so far has only been applied in workshops or as theoretical framework. Until now no spatially explicit backcasting model has been set up. The proposed backcasting model first creates a future scenario utilizing an Agent Based Model approach. Afterwards the model simulates backwards implemented as a Cellular Automaton. This is realized in a Python script and linked to the Open Source GIS software Quantum GIS. The general model is applied to a case study in Salzburg, Austria. The topic concerns sustainable spatial planning. The results of the model run show in time steps a successful backcasting of land-use classes from a future state back until present time.

Paper Nr: 3
Title:

Supply Chains Modelling and Simulation Framework - Graph-Driven Approach using Ontology-based Semantic Networks and Graph Database

Authors:

Mahmoud Elbattah and Owen Molloy

Abstract: Successful supply chains management has become a key factor for enterprises to achieve and maintain their competitive advantage. The increasing complexity and agility of supply chains are sustainably growing challenges. Simulation provides advantages over traditional analytical methods in planning and optimisation of supply chains. This paper presents a comprehensive framework for the modelling and simulation of supply chains. A graph-driven methodology is adopted considering supply chains as "Big Graphs". The research will utilise semantic networks, and develop a supply chain ontology to construct semantic-based models of supply chains. The framework proposes the use of graph databases for storing and maintaining complex supply chain models and ontologies. Furthermore, the framework will provide automatic generation of simulation models to help non-simulation experts. The applicability and validity of the proposed framework will be investigated within a case study of healthcare supply chains, during which a specific ontology for healthcare supply chains will be produced as well.

Paper Nr: 5
Title:

Uncertainty Quantification in Smart Grid Co-simulation Across Heterogeneous Model Domains

Authors:

Cornelius Steinbrink

Abstract: Smart Grids are complex systems that require systematic testing of the single components and their interaction on various scales. The Smart Energy Simulation and Automation Laboratory (SESA-Lab) is a flexible testing environment that supports modular interaction be- tween hardware and software based simulation. Its core is the real-time dynamic simulator eMEGAsim coupled with the modular Smart Grid simulation framework mosaik. The outlined PhD project aims at im- proving this coupling by increasing the accuracy of the data exchange and setting up a system for uncertainty quantification.

Paper Nr: 6
Title:

Novel Capacity Planning Methods for Flexible and Reconfigurable Assembly Systems

Authors:

Dávid Gyulai

Abstract: The importance of efficient planning methods is increasing with the evolution of manufacturing systems, since flexible and reconfigurable system structures require different planning approaches than the dedicated ones. The research presented in the paper is focused on production and capacity planning methods, which are able to cope with the dynamic changes that occur in the reconfigurable and flexible assembly systems. In the preceding publications of the author, some novel approaches were presented that support the management of modular reconfigurable resources and complex product portfolios.

Paper Nr: 7
Title:

Integrating Formal Verification and Simulation of Hybrid Systems - Rodin Multi-simulation Plug-in

Authors:

Vitaly Savicks, Michael Butler and John Colley

Abstract: The heterogeneous nature of hybrid systems, which consist of interleaving computational and physical domains, often represented by a hierarchy of different components, makes it difficult to use a single development tool. It is also coming into practice that an application of some formal method is required for the rigorous analysis and assurance of the safety of a developed system. This leads to an evident conclusion that a means of integrating the existing domain-specific tools and technologies with the emphasis on formal methods is required. In this work we focus on the idea of integrating formal modelling/verification with industrial-level simulation tools for different domains, as we think this can negate or minimise the limitations of the physical development in formal methods and the absence of the rigorous analysis in simulation tools. We propose an integration approach based on the co-simulation between Event-B formal method and a general class of physical simulators. Using the Functional Mock-up Interface standard we developed this idea into a Rodin Multi-Simulation tool for the Rodin platform.

Paper Nr: 9
Title:

Multi-Constraints and Single Objective Based Optimum Routes Planning for Assisted Evacuation - A Geographic Information System Based Solution and Simulation

Authors:

Md. Imran Hossain

Abstract: In an event of disaster, evacuation of the peoples who are at high risk, often become obvious to minimize the casualties. Among the evacuees, there are always special groups of people who are subject to severe mobility restrictions in terms of lack of personal transportation, limited financial resources, unfamiliarity with the area and its road network, physical and mental disabilities, language barrier etc. and therefore are at great risk of casualties. The responsible authorities (public safety agencies, police department etc.) for evacuation provide special evacuation units (vehicles) to collect and shift those special groups to a safe place which is called assisted evacuation. The route plan for each evacuation unit has significant effects on the efficiency of such assisted evacuation. The contemporary manual route planning with unknown spatial evacuee distribution hinders the performance of assisted evacuation in many folds. First of all, the evacuation units have to go through all the streets of a given area of evacuation which usually lead to a substantial waste of time and therefore become very inefficient especially when the evacuation is bounded by huge time pressure. Secondly, the manual process is unable to give estimation for the required/optimum number of evacuation units to cover all the evacuees who need assistance. And finally it cannot provide estimation for evacuees to be covered under certain time and resource constraints. Therefore, with a known spatial distribution of the evacuees, an automatic dynamic routing producing optimum path for the evacuation units would certainly preside over the any manual interventions in this case. The performance of assisted evacuation of an area depends on the route plan of each evacuation unit together with at least three major factors or variables: 1) Total available time (T): the time segment between the announcement of an evacuation and the actual disaster event, 2) Total available evacuation units (U) and 3) Number of evacuees (E): the number of the evacuees who need assistance. Therefore, a decision support system that can deliver the optimum paths for all the evacuation units in a dynamic way (alternative paths during run time) by fixing any two variables/factors and keeping the third as a goal would enable the incident manager for estimating the required resources and to take the right decision in a given evacuation scenario. Along with the optimized route plans the decision support system should answer the three basic questions. Firstly, how many evacuees (E) could be evacuated under certain time (T) and resource (U) constraints? Secondly, how many evacuation units (U) would be required to evacuate a certain number of evacuees (E) under a certain time (T) constraint? And finally, How long (T) would it take to evacuate certain amount of evacuees (E) with certain number of evacuation units (U)? This research project is therefore intended to develop such kind of decision support system (DSS). The DSS would be further tested, verified and validated by a suitable simulation technology.

Paper Nr: 11
Title:

Simulation Models for the Evaluation of Detection and Defense Protocols against Cyber Attacks - Preparation of Doctoral Consortium Contributions

Authors:

Lorena Paulina Valdiviezo

Abstract: Issues related to Cyber Security aspects, mainly focused on the security of computer systems and the services they offer, have gained considerable importance. The companies and even national governments, are incessantly affected by these issues to ensure the integrity of information systems and data managed through occurring in networked environments. Distributed Denial of Service (DDoS) flooding attack is one of the most diffused and effective threat against services and applications running over the Internet, in this sense, the research is primarily aimed at the study (assessment and validation) of hybrid models for detection, defense and response (R) for DDoS attacks, especially in the application layer, and the identification of new strategies. This research is based on modelling and simulating different scenarios using NeSSi2 and ns-3 as network simulation tools.