SMART CYBER- PHYSICAL SYSTEMS MINDAUGAS VASILJEVAS.

Slides:



Advertisements
Similar presentations
J. Kaiser University of Ulm Dept. Of Comp. Structures Jörg Kaiser Dept. Of Computer Structures University of Ulm And gets.
Advertisements

Programming Languages for End-User Personalization of Cyber-Physical Systems Presented by, Swathi Krishna Kilari.
Joint Access Point Placement and Channel Assignment for Wireless LANs Xiang Ling School of Communication and Information Engineering University.
Presented by: Thabet Kacem Spring Outline Contributions Introduction Proposed Approach Related Work Reconception of ADLs XTEAM Tool Chain Discussion.
February 21, 2008 Center for Hybrid and Embedded Software Systems Cyber-Physical Systems (CPS): Orchestrating networked.
A Mobile Infrastructure Based VANET Routing Protocol in the Urban Environment School of Electronics Engineering and Computer Science, PKU, Beijing, China.
Overview of PTIDES Project
Mohamed Hefeeda 1 School of Computing Science Simon Fraser University, Canada Multimedia Streaming in Dynamic Peer-to-Peer Systems and Mobile Wireless.
Software Engineering for Real- Time: A Roadmap H. Kopetz. Technische Universitat Wien, Austria Presented by Wing Kit Hor.
PTIDES: Programming Temporally Integrated Distributed Embedded Systems Yang Zhao, EECS, UC Berkeley Edward A. Lee, EECS, UC Berkeley Jie Liu, Microsoft.
Automated Analysis and Code Generation for Domain-Specific Models George Edwards Center for Systems and Software Engineering University of Southern California.
EECE Hybrid and Embedded Systems: Computation T. John Koo, Ph.D. Institute for Software Integrated Systems Department of Electrical Engineering and.
February 21, 2008 Center for Hybrid and Embedded Software Systems Organization Board of Directors Edward A. Lee, UC Berkeley.
April 16, 2009 Center for Hybrid and Embedded Software Systems PtidyOS: An Operating System based on the PTIDES Programming.
Causality Interface  Declares the dependency that output events have on input events.  D is an ordered set associated with the min ( ) and plus ( ) operators.
Presenter : Shih-Tung Huang Tsung-Cheng Lin Kuan-Fu Kuo 2015/6/15 EICE team Model-Level Debugging of Embedded Real-Time Systems Wolfgang Haberl, Markus.
February 23, 2012 Center for Hybrid and Embedded Software Systems Organization Board of Directors Edward A. Lee, EECS Thomas.
Design of Fault Tolerant Data Flow in Ptolemy II Mark McKelvin EE290 N, Fall 2004 Final Project.
7th Biennial Ptolemy Miniconference Berkeley, CA February 13, 2007 PTIDES: A Programming Model for Time- Synchronized Distributed Real-time Systems Yang.
Strategic Directions in Real- Time & Embedded Systems Aatash Patel 18 th September, 2001.
Tool Integration of Ptolemy II EE290N Class Project Haiyang Zheng May
DCL Concepts STL Concepts ContainerIteratorAlgorithmFunctorAdaptor What New Concepts are Needed for a “DCL”? (Distributed Computing Library) Distributed.
Project Results Colin Willcock, Project Coordinator for SEMAFOUR Project.
Software engineering on semantic web and cloud computing platform Xiaolong Cui Computer Science.
David Garlan Ivan Ruchkin Carnegie Mellon University Pittsburgh, PA, USA December 2014.
BAND-AiDe: A Tool for Cyber-Physical Oriented Analysis and Design of Body Area Networks and Devices Authors: Ayan Banerjee, Sailesh Kandula, Tridib Mukherjee.
Do we need theoretical computer science in software engineering curriculum: an experience from Uni Novi Sad Bansko, August 28, 2013.
, A Contract-Based Methodology for Aircraft Electric Power System Design IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS,pp ,ISSN ,9.
Cyber-Physical Systems: A New Frontier Nicole Ng 10/19/09 Tufts Wireless Laboratory Tufts University School Of Engineering.
Tufts Wireless Laboratory School Of Engineering Tufts University “Network QoS Management in Cyber-Physical Systems” Nicole Ng 9/16/20151 by Feng Xia, Longhua.
Structure of Study Programmes
EMBEDDED SYSTEMS FOUNDATIONS OF CYBER-PHYSICAL SYSTEMS PETER MARWEDEL Embedded System Design.
Distributed Intelligent Sensing and Control (DISC) for Automotive Factory Automation. Dr. Robert Brennan Dr. Ningxu Cai Mohammad Gholami.
Prediction-based Object Tracking and Coverage in Visual Sensor Networks Tzung-Shi Chen Jiun-Jie Peng,De-Wei Lee Hua-Wen Tsai Dept. of Com. Sci. and Info.
Department of Computer Science City University of Hong Kong Department of Computer Science City University of Hong Kong 1 Probabilistic Continuous Update.
Model-Driven Analysis Frameworks for Embedded Systems George Edwards USC Center for Systems and Software Engineering
1 Data Analytics & Energy Management Systems for Microgrids Reza Iravani Report on Project 1.2 and 2.2 NSMG-Net Annual Meeting.
How Smart Homes Learn The Evolution of the Networked Home and Household Marshini Chetty, Ja-Young Sung, and Rebecca E. Grinter Ubicomp 2007 Presenter:Brian.
PROV 504 NIKITHA VADDULA INTRODUCTION IMPORTANCE OF DISCIPLINE CURRENT ISSUES MAJOR ORGANIZATIONS PRE-EMINENT SCHOLARS SEMINAL WORKS CONNECTIONS.
College of Engineering Robert Akl, D.Sc. Department of Computer Science and Engineering.
Presentation on Issues and Challenges in Evaluation of Agent-Oriented Software Engineering Methodologies By: kanika singhal.
Extending Traditional Algorithms for Cyber-Physical Systems Sumeet Gujrati and Gurdip Singh Kansas State University.
Christian Sonntag TU Dortmund / euTeXoo GmbH Support Action CPSoS Platforms as a Driver for Smart Industrial Cyber-physical Systems of Systems Support.
Dr. Young J. Kim.  INCOSE Definition ( ◦ “An interdisciplinary approach & means to enable the realization of successful systems. It focuses.
1 CALL 6 Key Action IV Introduction and Action Lines: IV.1.2, IV.2.1, IV.2.2, IV.2.4 Brussels, 16. Jan 2001 Colette Maloney European Commission.
Real-Time Support for Mobile Robotics K. Ramamritham (+ Li Huan, Prashant Shenoy, Rod Grupen)
MMAC: A Mobility- Adaptive, Collision-Free MAC Protocol for Wireless Sensor Networks Muneeb Ali, Tashfeen Suleman, and Zartash Afzal Uzmi IEEE Performance,
A flexible simulator for control- dominated distributed real-time systems Johannes Petersson IDA/SaS/ESLAB Johannes Petersson IDA/SaS/ESLAB Master’s Thesis.
Internet of Things. IoT Novel paradigm – Rapidly gaining ground in the wireless scenario Basic idea – Pervasive presence around us a variety of things.
Adaptive Tracking in Distributed Wireless Sensor Networks Lizhi Yang, Chuan Feng, Jerzy W. Rozenblit, Haiyan Qiao The University of Arizona Electrical.
Efficient Group Key Management in Wireless LANs Celia Li and Uyen Trang Nguyen Computer Science and Engineering York University.
The 5th International Conference on Internet of Things 2015 Coex, Soeul, S. Korea Oct , 2015 Internet of Processes Vladimír Kebo, Center of Advanced.
Introduction to Hardware Verification ECE 598 SV Prof. Shobha Vasudevan.
Scheduling Messages with Deadlines in Multi-hop Real- time Sensor Networks Wei Song.
Multi-Task Assignment for CrowdSensing in Mobile Social Network Mingjun Xiao ∗, Jie Wu†, Liusheng Huang ∗, Yunsheng Wang‡, and Cong Liu§
Linking FMI-based Components with Ptolemy II’s Discrete Event Domain Introduction In the simulation of cyber-physical systems, event driven models with.
Euro-Par, HASTE: An Adaptive Middleware for Supporting Time-Critical Event Handling in Distributed Environments ICAC 2008 Conference June 2 nd,
Communication Scheme for Loosely Coupled Mobile User Groups in Wireless Sensor Fields Euisin Lee, Soochang Park, Fucai Yu, Min-Sook Jin, and Sang-Ha Kim.
February 11, 2016 Center for Hybrid and Embedded Software Systems Organization Faculty Edward A. Lee, EECS Alberto Sangiovanni-Vincentelli,
February 14, 2013 Center for Hybrid and Embedded Software Systems Organization Faculty Edward A. Lee, EECS Alberto Sangiovanni-Vincentelli,
ARTEMIS Industry Association Jan Lohstroh Secretary General, ARTEMIS Industry Association April 2016.
SRA 2016 – Strategic Research Challenges Design Methods, Tools, Virtual Engineering Jürgen Niehaus, SafeTRANS.
EE 249 Embedded Systems Design
Algorithms for Big Data Delivery over the Internet of Things
Model-Driven Analysis Frameworks for Embedded Systems
postgrad. Sergiy Korotunov prof. Galyna Tabunshchyk
An overview of the CHESS Center
Modeling and Simulation of WSN for Target Tracking
An overview of the CHESS Center
Automated Analysis and Code Generation for Domain-Specific Models
Presentation transcript:

SMART CYBER- PHYSICAL SYSTEMS MINDAUGAS VASILJEVAS

OUTLINE Smart Cyber-physical systems Smart Cyber-physical systems vs embedded systems Concept map of cyber-physical systems Structure of cyber-physical system Design process of cyber-physical systems 2

SMART CYBER-PHYSICAL SYSTEMS Cyber-physical systems are integrations of physical and computational processes. 3

CYBER-PHYSICAL SYSTEM VS. EMBEDDED SYSTEM Cyber-physical systems refer to next generation embedded systems Cyber-physical systems focus on physical and computational processes integration Embedded systems tend to be more on the computational elements 4

CYBER-PHYSICAL SYSTEMS – A CONCEPT MAP 5

CONCEPT MAP: DEFINITION PART 6

CONCEPT MAP: APPLICATION 7

CONCEPT MAP: REQUIRED CONCEPTS 8

STRUCTURE OF CYBER-PHYSICAL SYSTEM 9

DESIGN PROCESS OF CYBER-PHYSICAL SYSTEMS 10

MODELING CYBER-PHYSICAL SYSTEMS Continuous dynamics Discrete dynamics Hybrid systems 11

CONTINUOUS DYNAMICS Actor Models 12

DESCRETE DYNAMICS Finite State Machines 13

HYBRID SYSTEMS 14

DESIGNING CYBER-PHYSICAL SYSTEMS Model Based Design Process for Embedded System 15

10 STEPS MODEL BASED DESIGN PROCESS FOR CYBER-PHYSICAL SYSTEM MBD Step 1: State the Problem MBD Step 2: Model Physical Processes MBD Step 3: Characterize the Problem MBD Step 4: Derive a Control Algorithm MBD Step 5: Select Models of Computation MBD Step 6: Specify Hardware MBD Step 7: Simulate MBD Step 8: Construct MBD Step 9: Synthesize Software MBD Step 10: Verify, and Validate, and Test 16

CONCLUSION Cyber-Physical Systems (CPS) are integrations of computation, networking, and physical processes. CPS are heterogeneous and complex in nature. CPS are related to next generation embedded system. The difference between them is that CPS focus on physical and computational processes integration while embedded systems are more about computational processes. Model based design process is applied to CPS design. The key element of this process is a model. There are 3 types of models suitable to CPS: continuous models, discrete models and hybrid models. 17

REFERENCES E. A. Lee and S. A. Seshia, Introduction to Embedded Systems, A Cyber-Physical Systems Approach, ISBN , P. Asare, D. Broman, E. A. Lee, M. Torngren, S. Shyam Sunder. Cyber – Physical Systems – a Concept Map. Online Derler, P., Lee, E. A., & Vincentelli, A. S. (2012). Modeling cyber–physical systems. Proceedings of the IEEE, 100(1), Lee, E. A. (2008, May). Cyber physical systems: Design challenges. In Object Oriented Real-Time Distributed Computing (ISORC), th IEEE International Symposium on (pp ). IEEE. Jensen, J. C., Chang, D. H., & Lee, E. A. (2011, July). A model-based design methodology for cyber- physical systems. In Wireless Communications and Mobile Computing Conference (IWCMC), th International (pp ). IEEE. 18

THANK YOU FOR YOUR ATTENTION! 19

KLAUSIMAI AUDITORIJAI Kas yra kiberfizinės sistemos? Kuo skiriasi kiberfizinės ir įterptinės sistemos? Kokie yra tipinės kiberfizinės sistemos elementai? Kokio tipo modeliai taikomi kiberfinėse sistemose ir kokiems sistemos elementams jie taikomi? Iš kokių etapų susidaro 10 žingsnių į modelį orientuotas projektavimo procesas? 20