{"product_id":"cyber-physical-distributed-systems-isbn-9781119682677","title":"Cyber-Physical Distributed Systems","description":"\u003cb\u003eCYBER-PHYSICAL\u003c\/b\u003e DISTRIBUTED \u003cb\u003eSYSTEMS\u003c\/b\u003e \u003cp\u003e\u003cb\u003eGather detailed knowledge and insights into cyber-physical systems behaviors from a cutting-edge reference written by leading voices in the field\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIn \u003ci\u003eCyber-Physical Distributed Systems: Modeling, Reliability Analysis and Applications\u003c\/i\u003e, distinguished researchers and authors Drs. Huadong Mo, Giovanni Sansavini, and Min Xie deliver a detailed exploration of the modeling and reliability analysis of cyber physical systems through applications in infrastructure and energy and power systems. The book focuses on the integrated modeling of systems that bring together physical and cyber elements and analyzing their stochastic behaviors and reliability with a view to controlling and managing them.\u003c\/p\u003e \u003cp\u003eThe book offers a comprehensive treatment on the aging process and corresponding online maintenance, network degradation, and cyber-attacks occurring in cyber-physical systems. The authors include many illustrative examples and case studies based on real-world systems and offer readers a rich set of references for further research and study.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eCyber-Physical Distributed Systems\u003c\/i\u003e covers recent advances in combinatorial models and algorithms for cyber-physical systems modeling and analysis. The book also includes:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eA general introduction to traditional physical\/cyber systems, and the challenges, research trends, and opportunities for real cyber-physical systems applications that general readers will find interesting and useful\u003c\/li\u003e \u003cli\u003eDiscussions of general modeling, assessment, verification, and optimization of industrial cyber-physical systems\u003c\/li\u003e \u003cli\u003eExplorations of stability analysis and enhancement of cyber-physical systems, including the integration of physical systems and open communication networks\u003c\/li\u003e \u003cli\u003eA detailed treatment of a system-of-systems framework for the reliability analysis and optimal maintenance of distributed systems with aging components\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003ePerfect for undergraduate and graduate students in computer science, electrical engineering, cyber security, industrial and system engineering departments, \u003ci\u003eCyber-Physical Distributed Systems\u003c\/i\u003e will also earn a place on the bookshelves of students taking courses related to reliability, risk and control engineering from a system perspective. Reliability, safety and industrial control professionals will also benefit greatly from this book.\u003c\/p\u003e \u003cp\u003ePreface v\u003c\/p\u003e \u003cp\u003eList of Acronyms and Abbreviations ix\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e \u003cp\u003eIntroduction 1\u003c\/p\u003e \u003cp\u003eChallenges of Traditional Physical and Cyber Systems 1\u003c\/p\u003e \u003cp\u003eResearch Trends in Cyber-Physical Systems (CPSs) 3\u003c\/p\u003e \u003cp\u003eStability of CPSs 3\u003c\/p\u003e \u003cp\u003eReliability of CPSs 6\u003c\/p\u003e \u003cp\u003eOpportunities for CPS Applications 7\u003c\/p\u003e \u003cp\u003eManaging Reliability and Feasibility of CPSs 7\u003c\/p\u003e \u003cp\u003eEnsuring Cybersecurity of CPSs 9\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e \u003cp\u003eFundamentals of CPSs 13\u003c\/p\u003e \u003cp\u003eModels for Exploring CPSs 14\u003c\/p\u003e \u003cp\u003eControl-Block-Diagram of CPSs 14\u003c\/p\u003e \u003cp\u003eControl Signal in CPSs 14\u003c\/p\u003e \u003cp\u003eDegraded Actuator and Sensor 14\u003c\/p\u003e \u003cp\u003eTime-Varying Model of CPSs 15\u003c\/p\u003e \u003cp\u003eImplementation in TrueTime Simulator 16\u003c\/p\u003e \u003cp\u003eIntroduction of TrueTime Simulator 16\u003c\/p\u003e \u003cp\u003eArchitecture of CPSs in TrueTime 17\u003c\/p\u003e \u003cp\u003eEvaluation and Verification of CPSs 18\u003c\/p\u003e \u003cp\u003eCPS Performance Evaluation 18\u003c\/p\u003e \u003cp\u003eCPS Performance Index 18\u003c\/p\u003e \u003cp\u003eReliability Evaluation of CPSs 19\u003c\/p\u003e \u003cp\u003eCPS Model Verification 20\u003c\/p\u003e \u003cp\u003eCPS Performance Improvement 21\u003c\/p\u003e \u003cp\u003ePSO-Based Reliability Enhancement 22\u003c\/p\u003e \u003cp\u003eOptimal PID-Automatic Generation Control (AGC) 23\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e \u003cp\u003eStability Enhancement of CPSs 29\u003c\/p\u003e \u003cp\u003eIntegration of Physical and Cyber Models 30\u003c\/p\u003e \u003cp\u003eBasics of Wide-Area Power Systems (WAPS) 30\u003c\/p\u003e \u003cp\u003ePhysical Layer 30\u003c\/p\u003e \u003cp\u003eCyber Layer 31\u003c\/p\u003e \u003cp\u003eWAPS Realized in TrueTime 32\u003c\/p\u003e \u003cp\u003eAn Illustrative WAPS 33\u003c\/p\u003e \u003cp\u003eIllustrative Physical Layer 33\u003c\/p\u003e \u003cp\u003eIllustrative Cyber Layer 34\u003c\/p\u003e \u003cp\u003eIllustrative Integrated System 36\u003c\/p\u003e \u003cp\u003eSettings of Stability Analysis 36\u003c\/p\u003e \u003cp\u003eSettings of Delay Predictions 37\u003c\/p\u003e \u003cp\u003eSettings of Illustrative WAPS 37\u003c\/p\u003e \u003cp\u003eCases for Illustrative WAPS 38\u003c\/p\u003e \u003cp\u003eHidden Markov Model (HMM)-Based Stability Improvement 38\u003c\/p\u003e \u003cp\u003eOnline Smith Predictor 38\u003c\/p\u003e \u003cp\u003eInitialization of Discrete HMM (DHMM) 39\u003c\/p\u003e \u003cp\u003eParameter Estimation of DHMM 41\u003c\/p\u003e \u003cp\u003eDelay Prediction via DHMM 43\u003c\/p\u003e \u003cp\u003eSmith Predictor Structure 44\u003c\/p\u003e \u003cp\u003eDelay Predictions 44\u003c\/p\u003e \u003cp\u003eSettings of DHMM 45\u003c\/p\u003e \u003cp\u003ePrediction Comparison 46\u003c\/p\u003e \u003cp\u003ePerformance of Smith Predictor 47\u003c\/p\u003e \u003cp\u003eSettings of Smith Predictor 47\u003c\/p\u003e \u003cp\u003eAnalysis of Case 1 47\u003c\/p\u003e \u003cp\u003eAnalysis of Case 2 48\u003c\/p\u003e \u003cp\u003eStability Enhancement of Illustrative WAPS 49\u003c\/p\u003e \u003cp\u003eEigenvalue Analysis and Delay Impact 49\u003c\/p\u003e \u003cp\u003eSensitivity Analysis of Network Parameters 49\u003c\/p\u003e \u003cp\u003eOptimal AGC 50\u003c\/p\u003e \u003cp\u003eOptimal Controller Performance 50\u003c\/p\u003e \u003cp\u003eScenario 1 Analysis 51\u003c\/p\u003e \u003cp\u003eScenario 2 Analysis 51\u003c\/p\u003e \u003cp\u003eScenario 3 Analysis 52\u003c\/p\u003e \u003cp\u003eScenario 4 Analysis 52\u003c\/p\u003e \u003cp\u003eRobustness of Optimal AGC 52\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e \u003cp\u003eReliability Analysis of CPSs 65\u003c\/p\u003e \u003cp\u003eConceptual Distributed Generation Systems (DGSs) 65\u003c\/p\u003e \u003cp\u003eMathematical Model of Degraded Network 65\u003c\/p\u003e \u003cp\u003eModel of Transmission Delay 66\u003c\/p\u003e \u003cp\u003eModel of Packet Dropout 67\u003c\/p\u003e \u003cp\u003eScenarios of Degraded Network 68\u003c\/p\u003e \u003cp\u003eModeling and Simulation of DGSs 69\u003c\/p\u003e \u003cp\u003eDGS Model 69\u003c\/p\u003e \u003cp\u003ePreliminary Model 69\u003c\/p\u003e \u003cp\u003ePower Source Model 70\u003c\/p\u003e \u003cp\u003eData Interpolation 71\u003c\/p\u003e \u003cp\u003eReliability Estimation Via Optimal Power Flow (OPF) 71\u003c\/p\u003e \u003cp\u003eData Prediction 71\u003c\/p\u003e \u003cp\u003eMonte Carlo Simulation (MCS) of DGSs 73\u003c\/p\u003e \u003cp\u003eOPF of DGSs 74\u003c\/p\u003e \u003cp\u003eActual Cost and Reliability Analysis 75\u003c\/p\u003e \u003cp\u003eOPF of DGSs Against Unreliable Network 76\u003c\/p\u003e \u003cp\u003eSettings of Networked DGSs 76\u003c\/p\u003e \u003cp\u003eOPF Under Different Demand Levels 78\u003c\/p\u003e \u003cp\u003eOPF Under Entire Period 79\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e \u003cp\u003eMaintenance of Aging CPSs 87\u003c\/p\u003e \u003cp\u003eData-driven Degradation Model for CPSs 88\u003c\/p\u003e \u003cp\u003eDegraded Control System 88\u003c\/p\u003e \u003cp\u003eParameter Estimation via EM Algorithm 89\u003c\/p\u003e \u003cp\u003eLoad Frequency Control (LFC) Performance Criteria 90\u003c\/p\u003e \u003cp\u003eMaintenance Model and Cost Model 91\u003c\/p\u003e \u003cp\u003ePerformance Based Maintenance (PBM) Model 91\u003c\/p\u003e \u003cp\u003eCost Model 93\u003c\/p\u003e \u003cp\u003eApplications to DGSs 94\u003c\/p\u003e \u003cp\u003eOutput of Aging Generators 94\u003c\/p\u003e \u003cp\u003eImpact of Aging on DGSs 94\u003c\/p\u003e \u003cp\u003eSettings of Aging DGSs 94\u003c\/p\u003e \u003cp\u003eValidations of Generator Performance Indexes 95\u003c\/p\u003e \u003cp\u003eQuantitative Aging Impact 96\u003c\/p\u003e \u003cp\u003eApplications to Gas Turbine Plant 98\u003c\/p\u003e \u003cp\u003eSettings of Networked DGS Sensitivity Analysis of PBM 98\u003c\/p\u003e \u003cp\u003eImpact of Degradation on LFC 98\u003c\/p\u003e \u003cp\u003eNumerical Sensitivity Analysis 98\u003c\/p\u003e \u003cp\u003ePictorial Sensitivity Analysis 99\u003c\/p\u003e \u003cp\u003eOptimal Maintenance Strategy 100\u003c\/p\u003e \u003cp\u003eMaintenance Models Comparison 100\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e \u003cp\u003eGame Theory Based CPS Protection Plan 109\u003c\/p\u003e \u003cp\u003eVulnerability Model for CPSs 110\u003c\/p\u003e \u003cp\u003eMulti-state Attack-Defence Game 111\u003c\/p\u003e \u003cp\u003eBackgrounds of Game Model for CPSs 111\u003c\/p\u003e \u003cp\u003eMathematical Game Model 112\u003c\/p\u003e \u003cp\u003eAttack Consequence and Optimal Defence 113\u003c\/p\u003e \u003cp\u003eDamage Cost Model 113\u003c\/p\u003e \u003cp\u003eAttack Uncertainty 114\u003c\/p\u003e \u003cp\u003eOptimal Defence Plan 115\u003c\/p\u003e \u003cp\u003eApplications to DGSs with Uncertain Cyber-Attacks 116\u003c\/p\u003e \u003cp\u003eSettings of Game Model 116\u003c\/p\u003e \u003cp\u003eOptimal Protection with Constant Resource Allocation 116\u003c\/p\u003e \u003cp\u003eImpact Under Constant Case 116\u003c\/p\u003e \u003cp\u003eOptimal Constant Resource Allocation Fraction 117\u003c\/p\u003e \u003cp\u003eOptimal Protection with Dynamic Resource Allocation 118\u003c\/p\u003e \u003cp\u003eVulnerability Model Under Dynamic Case 119\u003c\/p\u003e \u003cp\u003eOptimal Dynamic Resource Allocation Fraction 120\u003c\/p\u003e \u003cp\u003eOptimization Results Justification 121\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e \u003cp\u003eBayesian Based Cyberteam Deployment 125\u003c\/p\u003e \u003cp\u003ePoisson Distribution based Cyber-attacks 125\u003c\/p\u003e \u003cp\u003eImpacts of DoS Attack 125\u003c\/p\u003e \u003cp\u003ePoisson Arrival Model Verification 126\u003c\/p\u003e \u003cp\u003eAverage Arrival Attacks 127\u003c\/p\u003e \u003cp\u003eCost of Multi-node Bandit Model 128\u003c\/p\u003e \u003cp\u003eRegret Function of Worst Case 128\u003c\/p\u003e \u003cp\u003eUpper Bound on Cost 129\u003c\/p\u003e \u003cp\u003eThompson-Hedge Algorithm 130\u003c\/p\u003e \u003cp\u003eHedge Algorithm 130\u003c\/p\u003e \u003cp\u003eDetails of Thompson-Hedge Algorithm 131\u003c\/p\u003e \u003cp\u003eSeparation of Target Regret 132\u003c\/p\u003e \u003cp\u003eUpper Bound of Λ_1 133\u003c\/p\u003e \u003cp\u003eUpper Bound of Λ_2 133\u003c\/p\u003e \u003cp\u003eUpper Bound of Regret R^TH 134\u003c\/p\u003e \u003cp\u003eApplications to Smart Grids 135\u003c\/p\u003e \u003cp\u003eOperation Cost of Smart Grid 135\u003c\/p\u003e \u003cp\u003eNumerical Analysis of Cost Sequences 137\u003c\/p\u003e \u003cp\u003ePerformance of Thompson-Hedge Algorithm 137\u003c\/p\u003e \u003cp\u003eComparison Study Against R.EXP3 137\u003c\/p\u003e \u003cp\u003eSensitivity to the Variation 140\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e \u003cp\u003eRecent Advances in CPS Modeling, Stability and Reliability 145\u003c\/p\u003e \u003cp\u003eModeling Techniques for CPS Components 145\u003c\/p\u003e \u003cp\u003eInverse Gaussian Process 145\u003c\/p\u003e \u003cp\u003eHitting Time to a Curved Boundary 146\u003c\/p\u003e \u003cp\u003eEstimator Error 147\u003c\/p\u003e \u003cp\u003eTheoretical Stability Analysis 148\u003c\/p\u003e \u003cp\u003eImpacts of Uncertainties 148\u003c\/p\u003e \u003cp\u003eSmall Gain Theorem based Stability Criteria 149\u003c\/p\u003e \u003cp\u003eRobust Stability Criteria 150\u003c\/p\u003e \u003cp\u003eGame Model for CPSs 151\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e \u003cp\u003eReferences 153\u003c\/p\u003e \u003cp\u003eIndex 177\u003c\/p\u003e \u003cp\u003e\u003cb\u003eHuadong Mo, PhD,\u003c\/b\u003e is Senior Lecturer in the School of Engineering and Information Technology at the University of New South Wales. He received his doctorate from the City University of Hong Kong in the area of cyber-physical system reliability engineering. \u003c\/p\u003e \u003cp\u003e\u003cb\u003eGiovanni Sansavini, PhD,\u003c\/b\u003e is Associate Professor at the Reliability and Risk Engineering Laboratory, Institute of Energy and Process Engineering, ETH Zurich, Switzerland. He is also the director of Reliability and Risk Engineering Laboratory, in the Institute of Energy and Process Engineering, Department of Mechanical and Process Engineering. He received his doctorate in nuclear engineering in 2010 from Politecnico di Milano, Italy, and a doctorate in engineering mechanics from Virginia Tech in Blacksburg in 2010.  \u003c\/p\u003e\u003cp\u003e\u003cb\u003eMin Xie, PhD,\u003c\/b\u003e is Chair Professor of Industrial Engineering in the Department of Advanced Design and Systems Engineering, at City University of Hong Kong. He received his doctorate in Quality Technology in 1987 from Linkoping University in Sweden and was elected as a Fellow of the IEEE in 2006.  \u003c\/p\u003e\u003cp\u003e\u003cb\u003eGather detailed knowledge and insights into cyber-physical systems behaviors from a cutting-edge reference written by leading voices in the field \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIn \u003ci\u003eCyber-Physical Distributed Systems: Modeling, Reliability Analysis and Applications\u003c\/i\u003e, distinguished researchers and authors Drs. Huadong Mo, Giovanni Sansavini, and Min Xie deliver a detailed exploration of the modeling and reliability analysis of cyber physical systems through applications in infrastructure and energy and power systems. The book focuses on the integrated modeling of systems that bring together physical and cyber elements and analyzing their stochastic behaviors and reliability with a view to controlling and managing them.  \u003c\/p\u003e\u003cp\u003eThe book offers a comprehensive treatment on the aging process and corresponding online maintenance, network degradation, and cyber-attacks occurring in cyber-physical systems. The authors include many illustrative examples and case studies based on real-world systems and offer readers a rich set of references for further research and study.  \u003c\/p\u003e\u003cp\u003e\u003ci\u003eCyber-Physical Distributed Systems\u003c\/i\u003e covers recent advances in combinatorial models and algorithms for cyber-physical systems modeling and analysis. The book also includes:  \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eA general introduction to traditional physical\/cyber systems, and the challenges, research trends, and opportunities for real cyber-physical systems applications that general readers will find interesting and useful\u003c\/li\u003e \u003cli\u003eDiscussions of general modeling, assessment, verification, and optimization of industrial cyber-physical systems\u003c\/li\u003e \u003cli\u003eExplorations of stability analysis and enhancement of cyber-physical systems, including the integration of physical systems and open communication networks\u003c\/li\u003e \u003cli\u003eA detailed treatment of a system-of-systems framework for the reliability analysis and optimal maintenance of distributed systems with aging components\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003ePerfect for undergraduate and graduate students in computer science, electrical engineering, cyber security, industrial and system engineering departments, \u003ci\u003eCyber-Physical Distributed Systems\u003c\/i\u003e will also earn a place on the bookshelves of students taking courses related to reliability, risk and control engineering from a system perspective. Reliability, safety and industrial control professionals will also benefit greatly from this book.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989018034405,"sku":"NP9781119682677","price":145.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119682677.jpg?v=1761782454","url":"https:\/\/k12savings.com\/products\/cyber-physical-distributed-systems-isbn-9781119682677","provider":"K12savings","version":"1.0","type":"link"}