Leveraging biologically inspired models for cyber-physical systems analysis

Cyber-physical systems (CPS) are systems composed of distributed sensors, physical actuators and controlling computers that are interconnected through a computer network. Notable examples include: electric utility “smart grids” that can sense and optimize power distribution, transportation systems, and healthcare and medical systems. As an emerging area of research, CPS engineering combines and extends the more mature disciplines of computing, control theory and communications engineering. As CPS complexity increases, system level trade studies become more challenging due to the combined interaction of the computing, network communications, and physical sensor and actuator elements. Although fundamentally different, complex CPS and biological systems share common attributes that suggest the use of similar modeling approaches. This work investigates the utility of employing modeling techniques developed for the analysis of biological systems for the system level trade study analysis of a distributed robotic wireless sensor network CPS.

[1]  Gurdip Singh,et al.  Models and algorithms for cyber-physical systems , 2013 .

[2]  F. H. Adler Cybernetics, or Control and Communication in the Animal and the Machine. , 1949 .

[3]  Mohammad Shahidul Hasan,et al.  Co-simulation of wireless networked control systems over mobile ad hoc network using SIMULINK and OPNET , 2009, IET Commun..

[4]  Shahram Sarkani,et al.  Leveraging Variability Modeling Techniques for Architecture Trade Studies and Analysis , 2014, Syst. Eng..

[5]  O. Schmitz,et al.  Foraging to balance conflicting demands: novel insights from grasshoppers under predation risk , 1997 .

[6]  Ravi Sunil,et al.  ENABLING SMART CLOUD SERVICES THROUGH REMOTE SENSING: AN INTERNET OF EVERYTHING ENABLER , 2015 .

[7]  Shu-Kun Lin,et al.  Shape and Structure, from Engineering to Nature , 2001, Entropy.

[8]  Edward A. Lee Cyber Physical Systems: Design Challenges , 2008, 2008 11th IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing (ISORC).

[9]  M. R. Arshad,et al.  An introduction to swarming robotics: application development trends , 2013, Artificial Intelligence Review.

[10]  C. A. Coello Coello,et al.  Evolutionary multi-objective optimization: a historical view of the field , 2006, IEEE Computational Intelligence Magazine.

[11]  Edward A. Lee,et al.  Modeling Cyber–Physical Systems , 2012, Proceedings of the IEEE.

[12]  Willem Bouten,et al.  Pareto front analysis of flight time and energy use in long-distance bird migration , 2007 .

[13]  Peter Palensky,et al.  Simulating Cyber-Physical Energy Systems: Challenges, Tools and Methods , 2014, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[14]  A. Messac,et al.  Generating Well-Distributed Sets of Pareto Points for Engineering Design Using Physical Programming , 2002 .

[15]  Gregory J. Barlow,et al.  Article in Press Robotics and Autonomous Systems ( ) – Robotics and Autonomous Systems Fitness Functions in Evolutionary Robotics: a Survey and Analysis , 2022 .

[16]  Andrew P. Sage,et al.  Handbook of Systems Engineering and Management , 2011 .

[17]  Yi Zhang,et al.  Study on Parameter Optimization Design of Drum Brake Based on Hybrid Cellular Multiobjective Genetic Algorithm , 2012 .

[18]  Jeffrey H. Smith Low-cost robotics for space exploration: a probabilistic trade space for biomorphic exploration devices , 2000, 2000 IEEE Aerospace Conference. Proceedings (Cat. No.00TH8484).

[19]  M.A. El-Sharkawi,et al.  Pareto Multi Objective Optimization , 2005, Proceedings of the 13th International Conference on, Intelligent Systems Application to Power Systems.

[20]  Jiafu Wan,et al.  A survey of Cyber-Physical Systems , 2011, 2011 International Conference on Wireless Communications and Signal Processing (WCSP).

[21]  Ronald W. Shonkwiler Mathematical Biology: An Introduction with Maple and Matlab , 2009 .

[22]  Chang Wook Ahn,et al.  On the practical genetic algorithms , 2005, GECCO '05.

[23]  John A. Stankovic,et al.  Research Directions for the Internet of Things , 2014, IEEE Internet of Things Journal.

[24]  D. DeAngelis,et al.  Modelling complex ecological dynamics : an introduction into ecological modelling for students, teachers & scientists , 2011 .

[25]  Kalyanmoy Deb,et al.  Multi-objective optimization using evolutionary algorithms , 2001, Wiley-Interscience series in systems and optimization.

[26]  Moshe T. Masonta,et al.  Bio-inspired energy and channel management in distributed wireless multi-radio networks , 2014 .

[27]  Leonard E. Miller,et al.  NASA systems engineering handbook , 1995 .

[28]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[29]  R. L. Keeney,et al.  Decisions with Multiple Objectives: Preferences and Value Trade-Offs , 1977, IEEE Transactions on Systems, Man, and Cybernetics.

[30]  Donald E. Grierson,et al.  Pareto multi-criteria decision making , 2008, Adv. Eng. Informatics.

[31]  Alessandro Saffiotti,et al.  Life-Long Optimization of the Symbolic Model of Indoor Environments for a Mobile Robot , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[32]  Sneha A. Dalvi,et al.  Internet of Things for Smart Cities , 2017 .

[33]  Marco Dorigo,et al.  Autonomous Self-Assembly in Swarm-Bots , 2006, IEEE Transactions on Robotics.

[34]  Alagan Anpalagan,et al.  Wireless Sensor Network Optimization: Multi-Objective Paradigm , 2015, Sensors.

[35]  Ju-Jang Lee,et al.  Multiobjective Optimization Approach for Sensor Arrangement in A Complex Indoor Environment , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[36]  A. Belegundu,et al.  Optimization Concepts and Applications in Engineering , 2011 .

[37]  Gabor Karsai,et al.  Toward a Science of Cyber–Physical System Integration , 2012, Proceedings of the IEEE.

[38]  Y. Charlie Hu,et al.  Deployment of mobile robots with energy and timing constraints , 2006, IEEE Transactions on Robotics.

[39]  Fernando Díaz del Río,et al.  A Tradeoff Analysis of a Cloud-Based Robot Navigation Assistant Using Stereo Image Processing , 2015, IEEE Transactions on Automation Science and Engineering.

[40]  Teresa Riesgo,et al.  Modelling and planning reliable wireless sensor networks based on multi-objective optimization genetic algorithm with changeable length , 2015, J. Heuristics.

[41]  Lothar Thiele,et al.  Quality Assessment of Pareto Set Approximations , 2008, Multiobjective Optimization.

[42]  Ryan Kelly,et al.  Budget‐constrained portfolio trades using multiobjective optimization , 2012, Syst. Eng..

[43]  Panganamala Ramana Kumar,et al.  Cyber–Physical Systems: A Perspective at the Centennial , 2012, Proceedings of the IEEE.

[44]  Panos Y. Papalambros,et al.  Principles of Optimal Design: Modeling and Computation , 1988 .

[45]  Siddhartha Kumar Khaitan,et al.  Design Techniques and Applications of Cyberphysical Systems: A Survey , 2015, IEEE Systems Journal.

[46]  Serge Kernbach,et al.  Handbook of Collective Robotics: Fundamentals and Challenges , 2013 .

[47]  Vijay Kumar,et al.  Sensors for micro bio robots via synthetic biology , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[48]  Dario Pompili,et al.  Dynamic Collaboration Between Networked Robots and Clouds in Resource-Constrained Environments , 2015, IEEE Transactions on Automation Science and Engineering.

[49]  Edward A. Lee,et al.  Introduction to Embedded Systems - A Cyber-Physical Systems Approach , 2013 .

[50]  Jay L. Devore,et al.  Modern Mathematical Statistics with Applications , 2021, Springer Texts in Statistics.

[51]  Ali Marjovi,et al.  Multi-robot exploration and fire searching , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[52]  E. David Ford,et al.  Using Multicriteria Analysis of Simulation Models to Understand Complex Biological Systems , 2011 .

[53]  Justin M. Bradley Toward Co-Design of Autonomous Aerospace Cyber-Physical Systems. , 2014 .

[54]  Robert J. Marks,et al.  Competitive Evolution of Tactical Multiswarm Dynamics , 2013, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[55]  Shengxiang Yang,et al.  Diversity Comparison of Pareto Front Approximations in Many-Objective Optimization , 2014, IEEE Transactions on Cybernetics.

[56]  Alexey Voinov,et al.  Systems Science and Modeling for Ecological Economics , 2008 .

[57]  N. Rashevsky,et al.  Mathematical biology , 1961, Connecticut medicine.