Distributed System Behavior Modeling of Urban Systems with - PowerPoint PPT Presentation

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Distributed System Behavior Modeling of Urban Systems with Ontologies, Rules and Many-to-Many Association Relationships Maria Coelho, Mark A. Austin, Mark Blackburn University of Maryland, Stevens Institute of Technology mecoelho@terpmail.umd.edu, austin@isr.umd.edu, mblackbu@stevens.edu Presentation at ICONS 2017, Venice, Italy April 22, 2017

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Overview Problem Statement 1 Related Work 2 Contributions 3 Semantic Modeling 4 Case Studies 1 and 2 5 Conclusions 6

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Problem Statement

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Interdependent Urban Networks Networks are heterogeneous, interwoven, dynamic. Waterway Disciplines want to operate Network independently in their domain. Transportation Network Achieving target levels of performance and correctness Information and of functionality requires Communications disciplines to coordinate activities at key points in Emergency Services system operation.

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Cascading Failures Disturbance in one system can impact other networks in unexpected, undesirable and costly ways. Often, infrastructure management systems do not allow manager of one system to access operations and conditions of another system. Decision making is complicated by presence of newfound system interactions, incomplete knowledge of system state, and break downs of communication among urban networks.

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Long-Term Project Objective: City Operating System Environmental Processes monitor Urban processes Monitoring monitor City Operating System Evaluation Space−time terrain Reasoning actions interacting with Relief Actions service infrastructures

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Short-Term Project Objective: Behavior Modeling Ability to model behavior of city-domain processes, and interactions among distributed system behaviors within a city. Physical Infrastructure Domain Business / Work Domain Transportation Domain Utility Network Urban Business Bus Routes Flows of: information, Flows of: information, goods, energy. goods, energy. Government Power Network Infrastructure − Business Business − Trans. Department Metro System Routes Mediator Mediator Flows of: information, Flows of: information, goods, energy. goods, energy. OptaPlanner: Real−Time Network Control and Planning for System Recovery Physical System Business System Transportation System −− Behavior control −− Behavior control −− Behavior control −− Resilience assessment −− Resilience assessment −− Resilience assessment −− Planning for receovery −− Planning for receovery −− Planning for receovery

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Benefits of Behavior Modeling Allows decision makers to understand: How failure in one network will impact other networks. What parts of a system are most vulnerable. Allows decision makers to assess: Sensitivity of systems to model parameter choices. Influence of resource constraints. Potential emergent interactions among systems.

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Solution Approach

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Systems of Systems Perspective Cities are System of Systems. City subsystems may have a preference to operating as independently as possible from the other subsystems. Strategic collaboration among subsystems is often needed to either avoid cascading failures across systems and/or recover from a loss of functionality. Home Taxi Airport Airplane Airport Taxi Destination

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Observing Urban Behavior Pedestrian Road Network Traffic Light Automobiles Traffic Control

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Ontologies, Rules, and Reasoning Mechanisms Design Rules and Reasoner Ontologies and Models Engineering Model Remarks System structures are Design Rules Classes System Structure modeled as networks and composite hierarchies Relationships of components. Reasoner Properties Behaviors will be associated with components. System Behavior define Discrete behavior will be Textual Requirements b modeled with finite a Instances c state machines. d verify Continuous behavior will be Individual Data represented by partial Requirement differential equations.

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Ontologies, Rules, and Reasoning Mechanisms Domain Rules Ontology Classes & Properties Engineering Model and Data TrafficControl.rules TrafficControl.owl Traffic control model TrafficLight.rules TrafficLight.owl Traffic light model Automobile.rules Automobile.owl Automobile model Pedestrian.rules Pedestrian.owl Pedestrian model RoadNetwork.rules RoadNetwork.owl Road network model load load data Abstraction load Reasoner Semantic Graphs graph transformation events load Cross−cutting (fundamental) Ontologies & Rules Spatial.owl Time.owl PhysicalQuantity.owl Spatial.rules Time.rules PhysicalQuantity.rules

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Related Work

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Glassbox Simulation Engine

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Graphs, Cellular Automata, and Ontologies Numerous researchers have studied the topology of urban environments from a graph theoretic standpoint. Other studies capture the temporal dynamics of cities with cellular automata, agent-based models, and fractals. Extensive studies have been conducted on the development of ontologies for the geographic information sector. Researchers have proposed so called smart city ontologies. A notable effort in the direction of ontologies developed alongside rules is the DogOnt ontology model.

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Contributions

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Contributions Framework for modeling concurrent, directed communication between all entities composing a system. System−to−System Communication Mediator−Enabled Communication Mediator Mechanisms for incorporating notions of space and time in the reasoning process.

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Semantic Modeling

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Introduction to the Semantic Web Extension to the World Wide Web Allows machines to access and share information. Relies on technical infrastructure below.

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Working with Jena and Jena Rules

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Distributed Behavior Modeling << abstract >> << abstract >> AbstractOntologyModel AbstractOntologyInterface message input message passing Semantic Model: Domain 1 Semantic Model: Domain 2 Interface: Domain 1 Mediator Interface: Domain 2 listener message passing listens for ModelChange events import import Rules for domain 1 Rules for domain 2 message input

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Case Study 1

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Family-School System Dynamics Family Domain Mediator Domain School System Domain listen Enrollment Enrollment listen Family Graph Family Interface School System School System Mediator Interface Model Graph Model Model Model Report Report Reasoner Reasoner import import school system family rules rules family − school import interaction rules

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Framework for Communication Family Domain School Domain Family A Elementary School Family B Mediator Middle School Family C High School

Problem Statement Related Work Contributions Semantic Modeling Case Studies 1 and 2 Conclusions Generation of Semantic Models