67. Sterbenz, J.P.G.; Hutchison, D.; Cetinkaya, E.K.; Jabbar, A.; Rohrer, J.P.; Schoeller, M.; Smith, P. Redundancy, diversity, and connectivity to achieve multilevel network resilience, survivability, and disruption tolerance invited paper. *Telecommun. Syst.* **2014**, *56*, 17–31. [CrossRef]

68. Rodriguez, M.; Kwiat, K.A.; Kamhoua, C.A. On the use of design diversity in fault tolerant and secure systems: A qualitative analysis. In Proceedings of the 2015 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA), Verona, NY, USA, 26–28 May 2015; pp. 1–8.

69. Rodriguez, M.; Kwiat, K.A.; Kamhoua, C.A. Modeling fault tolerant architectures with design diversity for secure systems. In Proceedings of the Military Communications Conference, MILCOM 2015, Tampa, FL, USA, 26–28 October 2015; pp. 1254–1263.

70. Lien, S.-Y. Resource-optimal heterogeneous machine-to-machine communications in software defined networking cyber-physical systems. *Wirel. Pers. Commun.* **2015**, *84*, 2215–2239. [CrossRef]

71. Iftikhar, M.U.; Weyns, D. Activforms: Active formal models for self-adaptation. In Proceedings of the 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, Hyderabad, India, 2–3 June 2014; pp. 125–134.

72. Uddin, I.; Rakib, A.; Ul Haque, H.M. A Framework for Implementing Formally Verified Resource-Bounded Smart Space Systems. *Mob. Netw. Appl.* **2017**, *22*, 289–304. [CrossRef]

73. Zhou, P.; Zuo, D.; Hou, K.-M.; Zhang, Z. A Decentralized Compositional Framework for Dependable Decision Process in Self-Managed Cyber Physical Systems. *Sensors* **2017**, *17*, 2580. [CrossRef] [PubMed]

74. Musil, A.; Musil, J.; Weyns, D.; Bures, T.; Muccini, H.; Sharaf, M. Patterns for Self-Adaptation in Cyber-Physical Systems. In *Multi-Disciplinary Engineering for Cyber-Physical Production Systems*; Springer: Cham, Switzerland, 2017; pp. 331–368.

75. Conti, S.; La Corte, A.; Nicolosi, R.; Rizzo, S. Impact of cyber-physical system vulnerability, telecontrol system availability and islanding on distribution network reliability. *Sustain. Energy Grids Netw.* **2016**, *6*, 143–151. [CrossRef]

76. Broman, D.; Zimmer, M.; Kim, Y.; Kim, H.; Cai, J.; Shrivastava, A.; Edwards, S.A.; Lee, E.A. Precision timed infrastructure: Design challenges. In Proceedings of the Electronic System Level Synthesis Conference (ESLsyn), Austin, TX, USA, 31 May–1 June 2013; pp. 1–6.

77. Lee, E.A. Computing needs time. *Commun. ACM* **2009**, *52*, 70–79. [CrossRef]

78. Patel, H.D.; Lickly, B.; Burgers, B.; Lee, E.A. *A Timing Requirements-Aware Scratchpad Memory Allocation Scheme for a Precision Timed Architecture*; DTIC Document; DTIC: Lincoln, NE, USA, 2008.

79. Zou, J.; Matic, S.; Lee, E.A. PtidyOS: A lightweight microkernel for Ptides real-time systems. In Proceedings of the 2012 IEEE 18th Real-Time and Embedded Technology and Applications Symposium (RTAS), Beijing, China, 16–19 April 2012; pp. 209–218.

80. Lickly, B.; Liu, I.; Kim, S.; Patel, H.D.; Edwards, S.A.; Lee, E.A. Predictable programming on a precision timed architecture. In Proceedings of the 2008 International Conference on Compilers, Architectures and Synthesis for Embedded Systems, Atlanta, GA, USA, 23–24 October 2008; pp. 137–146.

81. Bui, D.; Lee, E.; Liu, I.; Patel, H.; Reineke, J. Temporal isolation on multiprocessing architectures. In Proceedings of the 48th Design Automation Conference, San Diego, CA, USA, 5–9 June 2011; pp. 274–279.

82. Dierikx, E.F.; Wallin, A.E.; Fordell, T.; Myyry, J.; Koponen, P.; Merimaa, M.; Pinkert, T.J.; Koelemeij, J.C.; Peek, H.Z.; Smets, R. White Rabbit Precision Time Protocol on Long-Distance Fiber Links. *IEEE Trans. Ultrason. Ferroelectr. Freq. Control* **2016**, *63*, 945–952. [CrossRef] [PubMed]

83. Elattar, M.; Dürkop, L.; Jasperneite, J. Utilizing LTE QoS features to provide a reliable access network for cyber-physical systems. In Proceedings of the 2015 IEEE 13th International Conference on Industrial Informatics (INDIN), Cambridge, UK, 22–24 July 2015; pp. 956–961.

84. Aristova, N.I. Ethernet in industrial automation: Overcoming obstacles. *Autom. Remote Control* **2016**, *77*, 881–894. [CrossRef]

85. Watteyne, T.; Handziski, V.; Vilajosana, X.; Duquennoy, S.; Hahm, O.; Baccelli, E.; Wolisz, A. Industrial wireless ip-based cyber-physical systems. *Proc. IEEE* **2016**, *104*, 1025–1038. [CrossRef]

86. Eidson, J.; Lee, E.A.; Matic, S.; Seshia, S.A.; Zou, J. A time-centric model for cyber-physical applications. In Proceedings of the Workshop on Model Based Architecting and Construction of Embedded Systems (ACES-MB), Aachen, Germany, 2–8 October 2010; pp. 21–35.
87. Abella, J.; Hernandez, C.; Quiñones, E.; Cazorla, F.J.; Conmy, P.R.; Azkarate-askasua, M.; Perez, J.; Mezzetti, E.; Vardanega, T. WCET analysis methods: Pitfalls and challenges on their trustworthiness. In Proceedings of the 10th IEEE International Symposium on Industrial Embedded Systems (SIES), Siegen, Germany, 8–10 June 2015; pp. 1–10.

88. Wilhelm, R.; Engblom, J.; Ermedahl, A.; Holsti, N.; Thesing, S.; Whalley, D.; Bernat, G.; Ferdinand, C.; Heckmann, R.; Mitra, T. The worst-case execution-time problem—overview of methods and survey of tools. *ACM Trans. Embed. Comput. Syst.* **2008**, *7*, 36. [CrossRef]

89. Krishna, C. Fault-tolerant scheduling in homogeneous real-time systems. *ACM Comput. Surv.* **2014**, *46*, 48. [CrossRef]

90. Nelaturi, S.; de Kleer, J.; Shapiro, V. Combinatorial Models for Heterogeneous System Composition and Analysis. In Proceedings of the 2016 11th System of Systems Engineering Conference (SoSE) 2016, Kongsberg, Norway, 12–16 June 2016.

91. Gössler, G.; Sifakis, J. Composition for component-based modeling. *Sci. Comput. Program.* **2005**, *55*, 161–183. [CrossRef]

92. Sztipanovits, J.; Koutsoukos, X.; Karsai, G.; Kottenstette, N.; Antsaklis, P.; Gupta, V.; Goodwine, B.; Baras, J.; Wang, S. Toward a science of cyber-physical system integration. *Proc. IEEE* **2011**, *100*, 29–44. [CrossRef]

93. Nuzzo, P.; Sangiovanni-Vincentelli, A.L.; Bresolin, D.; Geretti, L.; Villa, T. A platform-based design methodology with contracts and related tools for the design of cyber-physical systems. *Proc. IEEE* **2015**, *103*, 2104–2132. [CrossRef]

94. Attie, P.; Baranov, E.; Bliudze, S.; Jaber, M.; Sifakis, J. A general framework for architecture composability. *Form. Asp. Comput.* **2016**, *28*, 207–231. [CrossRef]

95. Seshia, S.A. Combining induction, deduction, and structure for verification and synthesis. *Proc. IEEE* **2015**, *103*, 2036–2051. [CrossRef]

96. Tripakis, S. Compositionality in the science of system design. *Proc. IEEE* **2016**, *104*, 960–972. [CrossRef]

97. Chen, T.; Chilton, C.; Jonsson, B.; Kwiatkowska, M. A compositional specification theory for component behaviours. In *European Symposium on Programming*; Springer: Berlin/Heidelberg, Germany, 2012; pp. 148–168.

98. Le, T.T.H.; Passerone, R.; Fahrenberg, U.; Legay, A. Contract-Based Requirement Modularization via Synthesis of Correct Decompositions. *ACM Trans. Embed. Comput. Syst.* **2016**, *15*. [CrossRef]

99. Laird, L.M.; Brennan, M.C. *Software Measurement and Estimation: A Practical Approach*; John Wiley & Sons: New York, NY, USA, 2006; Volume 2.

100. Henry, S.; Kafura, D. Software structure metrics based on information flow. *IEEE Trans. Softw. Eng.* **1981**, *SE-7*, 510–518. [CrossRef]

101. Halstead, M.H. *Elements of Software Science (Operating and Programming Systems Series)*; Elsevier Science Inc.: New York, NY, USA, 1977.

102. Isermann, R. *Fault-Diagnosis Systems: An Introduction from Fault Detection to Fault Tolerance*; Springer Science & Business Media: New York, NY, USA, 2006.

103. Stapelberg, R.F. *Handbook of Reliability, Availability, Maintainability and Safety in Engineering Design*; Springer Science & Business Media: New York, NY, USA, 2009.

104. Biroli, A. *Reliability Engineering: Theory and Practice*, 7th ed.; Springer: New York, NY, USA, 2002.

105. Hasan, O.; Ahmed, W.; Tahar, S.; Hamdi, M.S.; Simos, T.E.; Tsitouras, C. Reliability block diagrams based analysis: A survey. In *AIP Conference Proceedings*; AIP Publishing: New York, NY, USA, 2015; p. 850129.

106. Ruijters, E.; Stoelinga, M. Fault tree analysis: A survey of the state-of-the-art in modeling, analysis and tools. *Comput. Sci. Rev.* **2015**, *15–16*, 29–62. [CrossRef]

107. Kabir, S. An overview of fault tree analysis and its application in model based dependability analysis. *Expert Syst. Appl.* **2017**, *77*, 114–135. [CrossRef]

108. Höfig, K.; Domis, D. Failure-dependent execution time analysis. In Proceedings of the Joint ACM SIGSOFT Conference–QoSA and ACM SIGSOFT Symposium–ISARCS on Quality of Software Architectures–QoSA and Architecting Critical Systems–ISARCS, Boulder, CO, USA, 20–24 June 2011; pp. 115–122.

109. Ahmed, W.; Hasan, O.; Tahar, S. Formal dependability modeling and analysis: A survey. In *International Conference on Intelligent Computer Mathematics*; Springer: Berlin, Germany, 2016; pp. 132–147.
110. Ma, Z.; Fu, X.; Yu, Z. Object-oriented petri nets based formal modeling for high-confidence cyber-physical systems. In Proceedings of the 2012 8th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM), Shanghai, China, 21–23 September 2012; pp. 1–4.

111. Bryant, B.R.; Gray, J.; Mernik, M.; Clarke, P.J.; France, R.B.; Karsai, G. Challenges and Directions in Formalizing the Semantics of Modeling Languages. *Comput. Sci. Inf. Syst.* **2011**, *8*, 225–253. [CrossRef]

112. Abbas, A.M.; Tsang, E.P.; Nasri, A.H. Depict: A high-level formal language for modeling constraint satisfaction problems. *Int. J. Autom. Comput.* **2008**, *5*, 208–216. [CrossRef]

113. Feiler, P.H.; Lewis, B.A.; Vestal, S. The SAE Architecture Analysis & Design Language (AADL) a standard for engineering performance critical systems. In Proceedings of the 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control, Munich, Germany, 4–6 October 2006; pp. 1206–1211.

114. Aissa, A.B.; Abercrombie, R.K.; Sheldon, F.T.; Mili, A. Quantifying the impact of unavailability in cyber-physical environments. In Proceedings of the Computational Intelligence in Cyber Security (CICS), 2014 IEEE Symposium on, Orlando, FL, USA, 9–12 December 2014; pp. 1–8.

115. Kozat, U.C.; Liang, G.; Kokten, K.; Tapolcai, J. On Optimal Topology Verification and Failure Localization for Software Defined Networks. *IEEE-ACM Trans. Netw.* **2016**, *24*, 2931–2944. [CrossRef]

116. Rungger, M.; Tabuada, P. A symbolic approach to the design of robust cyber-physical systems. In Proceedings of the 2013 IEEE 52nd Annual Conference on Decision and Control (CDC), Firenze, Italy, 10–13 December 2013; pp. 3932–3937.

117. Takai, S.; Kumar, R. Verification of generalized inference diagnosability for decentralized diagnosis in discrete event systems. In Proceedings of the 2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA), Luxembourg, 8–11 September 2015; pp. 1–8.

118. Ganin, A.A.; Massaro, E.; Gutfraind, A.; Steen, N.; Keisler, J.M.; Kott, A.; Mangoubi, R.; Linkov, I. Operational resilience: Concepts, design and analysis. *Sci. Rep.* **2016**, *6*, 19540. [CrossRef] [PubMed]

119. Laibinis, L.; Klionskiy, D.; Troubitsyna, E.; Dorokhov, A.; Lilius, J.; Kupriyanov, M. Modelling Resilience of Data Processing Capabilities of CPS. In *Software Engineering for Resilient Systems*; Majzik, I., Vieira, M., Eds.; Springer: Berlin/Heidelberg, Germany, 2014; Volume 8785, pp. 55–70.

120. Mashkoor, A.; Hasan, O. Formal probabilistic analysis of cyber-physical transportation systems. In Proceedings of the International Conference on Computational Science and Its Applications, Bahia, Brazil, 18–21 June 2012; pp. 419–434.

121. Marashi, K.; Sarvestani, S.S. Towards comprehensive modeling of reliability for smart grids: Requirements and challenges. In Proceedings of the 2014 IEEE 15th International Symposium on High-Assurance Systems Engineering (HASE), Miami Beach, FL, USA, 9–11 January 2014; pp. 105–112.

122. Han, Y.; Wen, Y.; Guo, C.; Huang, H. Incorporating Cyber Layer Failures in Composite Power System Reliability Evaluations. *Energies* **2015**, *8*, 9064–9086. [CrossRef]

123. Hu, X.; Liu, S.; Chen, G.; Jiang, C. Dependability Modelling and Evaluation of Cyber-Physical Systems: A Model-Driven Perspective. In Proceedings of the 1st International Workshop on Cloud Computing and Information Security, Shanghai, China, 9 November–11 November 2013; Atlantis Press: Paris, France, 2013.

124. Di Giandomenico, F.; Kwiatkowska, M.; Martinucci, M.; Masci, P.; Qu, H. Dependability Analysis and Verification for CONNECTed Systems. In *Leveraging Applications of Formal Methods, Verification, and Validation*; Margaria, T., Steffen, B., Eds.; Springer: Berlin/Heidelberg, Germany, 2010; Volume 6416, pp. 263–277.

125. Sanislav, T.; Mois, G.; Miclea, L. An approach to model dependability of cyber-physical systems. *Microprocess. Microsyst.* **2016**, *41*, 67–76. [CrossRef]

126. Bozzano, M.; Cimatti, A.; Katoen, J.-P.; Nguyen, V.Y.; Noll, T.; Roveri, M. Safety, dependability and performance analysis of extended AADL models. *Comput. J.* **2011**, *54*, 754–775. [CrossRef]

127. Esteve, M.-A.; Katoen, J.-P.; Viet Yen, N.; Postma, B.; Yushtein, Y. Formal Correctness, Safety, Dependability, and Performance Analysis of a Satellite. In Proceedings of the 2012 34th International Conference on Software Engineering (ICSE), Zurich, Switzerland, 2–9 June 2012; pp. 1022–1031.

128. Dal Lago, L.; Ferrante, O.; Passerone, R.; Ferrari, A. Dependability Assessment of SOA-based CPS with Contracts and Model-Based Fault Injection. *IEEE Trans. Ind. Inform.* **2018**, *14*, 360–369. [CrossRef]

129. Ghezzi, C. Dependability of Adaptable and Evolvable Distributed Systems. In *Formal Methods for the Quantitative Evaluation of Collective Adaptive Systems*; Springer: Berlin, Germany, 2016; pp. 36–60.
130. Tundis, A.; Buffoni, L.; Fritzson, P.; Garro, A. Model-Based Dependability Analysis of Physical Systems with Modelica. *Model. Simul. Eng.* **2017**, *2017*, 1578043. [CrossRef]

131. Provan, G. A Contracts-Based Framework for Systems Modeling and Embedded Diagnostics. In *Software Engineering and Formal Methods, Sefm 2014; Canal, C., Idani, A., Eds.; Springer: Berlin/Heidelberg, Germany, 2015; Volume 8938, pp. 131–143.

132. Hu, F.; Lu, Y.; Vasilakos, A.V.; Hao, Q.; Ma, R.; Patil, Y.; Zhang, T.; Lu, J.; Li, X.; Xiong, N.N. Robust cyber-physical systems: Concept, models, and implementation. *Future Gener. Comput. Syst.* **2016**, *56*, 449–475. [CrossRef]

133. Silva, L.C.; Almeida, H.O.; Perkusich, A.; Perkusich, M. A Model-Based Approach to Support Validation of Medical Cyber-Physical Systems. *Sensors* **2015**, *15*, 27625–27670. [CrossRef] [PubMed]

134. Sanislav, T.; Mois, G. A dependability analysis model in the context of cyber-physical systems. In Proceedings of the 2017 18th International Carpathian Control Conference (ICCC), Sinaia, Romania, 28–31 May 2017; pp. 146–150.

135. Tundis, A.; Ferretto, D.; Garro, A.; Brusa, E.; Mühlhäuser, M. Dependability assessment of a deicing system through the RAMSAS method. In Proceedings of the 2017 IEEE International Systems Engineering Symposium (ISSE), Vienna, Austria, 11–13 October 2017; pp. 1–8.

136. Jiang, Y.; Song, H.; Yang, Y.; Liu, H.; Gu, M.; Guan, Y.; Sun, J.; Sha, L. Dependable Model-driven Development of CPS: From Stateflow Simulation to Verified Implementation. *ACM Trans. Cyber-Phys. Syst.* **2018**, *3*, 1–31. [CrossRef]

137. Tsigkanos, C.; Kehrer, T.; Ghezzi, C. Modeling and verification of evolving cyber-physical spaces. In Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering, Paderborn, Germany, 4–8 September 2017; pp. 38–48.

138. Fritzson, P. Model-based development of sustainable cyber-physical systems including requirement formalization using the openModelica model-based development toolkit. In Proceedings of the 10th European Conference on Software Architecture Workshops, Copenhagen, Denmark, 28 November–2 December 2016; p. 1.

139. Hachicha, M.; Dammak, E.; Halima, R.B.; Kacem, A.H. A correct by construction approach for modeling and formalizing self-adaptive systems. In Proceedings of the 2016 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), Shanghai, China, 30 May–1 June 2016; pp. 379–384.

140. Arcaini, P.; Riccobene, E.; Scandurra, P. Modeling and validating self-adaptive service-oriented applications. *ACM SIGAPP Appl. Comput. Rev.* **2015**, *15*, 35–48. [CrossRef]

141. Brito, A.V.; Negreiros, A.V.; Roth, C.; Sander, O.; Becker, J. Development and Evaluation of Distributed Simulation of Embedded Systems using Ptolemy and HLA. In Proceedings of the 17th IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications, Delft, The Netherlands, 30 October–1 November 2013; pp. 189–196.

142. Conzon, D.; Brizzi, P.; Kasinathan, P.; Pastrone, C.; Pramudianto, F.; Cultrona, P. Industrial application development exploiting IoT Vision and Model Driven programming. In Proceedings of the 2015 8th International Conference on Intelligence in Next Generation Networks, Paris, France, 17–19 February 2015; pp. 168–175.

143. Whittle, J.; Hutchinson, J.; Rouncefield, M. The state of practice in model-driven engineering. *Softw. IEEE* **2014**, *31*, 79–85. [CrossRef]

144. Kroiss, C.; Bures, T. Logic-based modeling of information transfer in cyber-physical multi-agent systems. *Future Gener. Comput. Syst.* **2016**, *56*, 124–139. [CrossRef]

145. Xi, Z. Physically Informed Assertions for Cyber Physical Systems Development and Debugging. In Proceedings of the 2014 IEEE International Conference on Pervasive Computing and Communication Workshops (PERCOM WORKSHOPS), Budapest, Hungary, 24–28 March 2014; pp. 181–183.

146. Anier, A.; Vain, J.; Tsiopoulos, L. DTRON: A tool for distributed model-based testing of time critical applications. *Proc. Est. Acad. Sci.* **2017**, *66*, 75–88. [CrossRef]

147. Hou, Y.; Zhao, Y.; Wagh, A.; Zhang, L.; Qiao, C.; Hulme, K.F.; Wu, C.; Sadek, A.W.; Liu, X. Simulation-Based Testing and Evaluation Tools for Transportation Cyber-Physical Systems. *IEEE Trans. Veh. Technol.* **2016**, *65*, 1098–1108. [CrossRef]
148. Slåtten, V.; Herrmann, P.; Kraemer, F.A. Model-Driven Engineering of Reliable Fault-Tolerant Systems-A State-of-the-Art Survey. *Adv. Comput.* **2013**, *91*, 119-205.

149. Solé, M.; Muntés-Mulero, V.; Rana, A.I.; Estrada, G. Survey on Models and Techniques for Root-Cause Analysis. *arXiv*, 2017; arXiv:1701.08546.

150. Völter, M.; Stahl, T.; Bettin, J.; Haase, A.; Helsen, S. *Model-Driven Software Development: Technology, Engineering, Management*; John Wiley & Sons: New York, NY, USA, 2013.

151. Brambilla, M.; Cabot, J.; Wimmer, M. Model-driven software engineering in practice. *Synth. Lect. Softw. Eng.* **2012**, *1*, 1-182. [CrossRef]

152. Kordon, F.; Hugues, J.; Canals, A.; Dohet, A. *Embedded Systems: Analysis and Modeling with SysML, UML and AADL*; John Wiley & Sons: New York, NY, USA, 2013.

153. Wehrmeister, M.A.; Pereira, C.E.; Rammig, F.J. Aspect-oriented model-driven engineering for embedded systems applied to automation systems. *IEEE Trans. Ind. Inform.* **2013**, *9*, 2373-2386. [CrossRef]

154. Lee, E.A. The Past, Present and Future of Cyber-Physical Systems: A Focus on Models. *Sensors* **2015**, *15*, 4837-4869. [CrossRef] [PubMed]

155. Weber, P.; Medina-Oliva, G.; Simon, C.; Iung, B. Overview on Bayesian networks applications for dependability, risk analysis and maintenance areas. *Eng. Appl. Artif. Intell.* **2012**, *25*, 671-682. [CrossRef]

156. Francalanza, E.; Borg, J.; Constantinescu, C. A knowledge-based tool for designing cyber physical production systems. *Comput. Ind.* **2017**, *84*, 39-58. [CrossRef]

157. Weyns, D.; Ahmad, T. Claims and evidence for architecture-based self-adaptation: A systematic literature review. In *European Conference on Software Architecture*; Springer: New York, NY, USA, 2013; pp. 249-265.

158. Kakousis, K.; Paspallis, N.; Papadopoulos, G.A. A survey of software adaptation in mobile and ubiquitous computing. *Enterp. Inf. Syst.* **2010**, *4*, 355-389. [CrossRef]

159. Roy, S.; Biswas, S.; Chaudhuri, S.S. Nature-inspired swarm intelligence and its applications. *Int. J. Mod. Educ. Comput. Sci.* **2014**, *6*, 55. [CrossRef]

160. Mavrovouniotis, M.; Li, C.; Yang, S. A survey of swarm intelligence for dynamic optimization: Algorithms and applications. *Swarm Evol. Comput.* **2017**, *33*, 1-17. [CrossRef]

161. Parpinelli, R.S.; Lopes, H.S. New inspirations in swarm intelligence: A survey. *Int. J. Bio-Inspir. Comput.* **2011**, *3*, 1-16. [CrossRef]

162. Muccini, H.; Sharaf, M.; Weyns, D. Self-adaptation for cyber-physical systems: A systematic literature review. In *Proceedings of the 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems*, Austin, TX, USA, 16-17 May 2016; pp. 75-81.

163. Chen, Y.; Zhou, J.; Guo, M. A context-aware search system for Internet of Things based on hierarchical context model. *Telecommun. Syst.* **2016**, *62*, 77-91. [CrossRef]

164. Li, Y.; Chai, K.K.; Chen, Y.; Loo, J. Smart Duty Cycle Control with Reinforcement Learning for Machine to Machine Communications. In *Proceedings of the 2015 IEEE International Conference on Communication Workshop (ICCW)*, London, UK, 8-12 June 2015; pp. 1458-1463.

165. Gu, S.; Holly, E.; Lillicrap, T.; Levine, S. Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates. *arXiv*, 2016; arXiv:1610.00633.

166. Toser, Z.; Lorincz, A. The Cyber-Physical System Approach Towards Artificial General Intelligence: The Problem of Verification. In *Artificial General Intelligence*; Bieger, J., Goertzel, B., Potapov, A., Eds.; Springer: Berlin/Heidelberg, Germany, 2015; Volume 9205, pp. 373-383.

167. Mi, M.; Zolotov, I. Comparison between multi-class classifiers and deep learning with focus on industry 4.0. In *Proceedings of the 2016 Cybernetics & Informatics (K&I)*, Levoča, Slovakia, 2-5 February 2016; pp. 1-5.

168. Wang, H.; Li, Q.; Yi, F.; Li, Z.; Sun, L. Influential spatial facility prediction over large scale cyber-physical vehicles in smart city. *Eurasip J. Wirel. Commun. Netw.* **2016**, *2016*, 103. [CrossRef]

169. Varshney, K.R.; Alemzadeh, H. On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products. *arXiv*, 2016; arXiv:1610.01256.

170. Maier, A. Online passive learning of timed automata for cyber-physical production systems. In *Proceedings of the 2014 12th IEEE International Conference on Industrial Informatics (INDIN)*, Porto Alegre, Brazil, 27-30 July 2014; pp. 60-66.

171. Ruchkin, I.; Samuel, S.; Schmerl, B.; Rico, A.; Garlan, D. Challenges in physical modeling for adaptation of cyber-physical systems. In *Proceedings of the 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT)*, Reston, VA, USA, 12-14 December 2016; pp. 210-215.
172. Macias-Escriva, F.D.; Haber, R.; del Toro, R.; Hernandez, V. Self-adaptive systems: A survey of current approaches, research challenges and applications. *Expert Syst. Appl.* **2013**, *40*, 7267-7279. [CrossRef]

173. Moreno, G.A.; Cámara, J.; Garlan, D.; Schmerl, B. Proactive self-adaptation under uncertainty: A probabilistic model checking approach. In Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering, Bergamo, Italy, 30 August-4 September 2015; pp. 1-12.

174. Seshia, S.A.; Hu, S.; Li, W.; Zhu, Q. Design Automation of Cyber-Physical Systems: Challenges, Advances, and Opportunities. *IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.* **2017**, *36*, 1421-1434. [CrossRef]

175. Amodei, D.; Olah, C.; Steinhardt, J.; Christiano, P.; Schulman, J.; Mané, D. Concrete problems in AI safety. *arXiv*, 2016; arXiv:1606.06565.

176. Seshia, S.A.; Sadigh, D.; Sastry, S.S. Towards verified artificial intelligence. *arXiv*, 2016; arXiv:1606.08514.

177. Khan, F.; Rathnayaka, S.; Ahmed, S. Methods and models in process safety and risk management: Past, present and future. *Process Saf. Environ. Prot.* **2015**, *98*, 116-147. [CrossRef]

178. Vose, D. *Risk Analysis: A Quantitative Guide*; John Wiley & Sons: New York, NY, USA, 2008.

179. Weyns, D.; Iftikhar, M.U.; De La Iglesia, D.G.; Ahmad, T. A survey of formal methods in self-adaptive systems. In Proceedings of the Fifth International Conference on Computer Science and Software Engineering, Montreal, QC, Canada, 27-29 June 2012; pp. 67-79.

180. Babaee, R.; Babamir, S.M. Runtime verification of service-oriented systems: A well-rounded survey. *Int. J. Web Grid Serv.* **2013**, *9*, 213-267. [CrossRef]

181. Singh, I.; Lee, S.-W. Self-adaptive requirements for intelligent transportation system: A case study. In Proceedings of the 2017 International Conference on Information and Communication Technology Convergence (ICTC), Jeju Island, Korea, 18-20 October 2017; pp. 520-526.

182. Camilli, M.; Gargantini, A.; Scandurra, P. Zone-based formal specification and timing analysis of real-time self-adaptive systems. *Sci. Comput. Program.* **2018**, *159*, 28-57. [CrossRef]

183. Fu, Y.; Shuvo, M.H. An Approach to Analyzing Adaptive Intelligent Vehicle System Using SMT Solver. In Proceedings of the 2016 International Conference on Control, Decision and Information Technologies (CoDIT), St. Julian's, Malta, 6-8 April 2016; pp. 313-319.

184. Bersani, M.M.; García-Valls, M. The cost of formal verification in adaptive CPS. An example of a virtualized server node. In Proceedings of the 2016 IEEE 17th International Symposium on High Assurance Systems Engineering (HASE), Orlando, FL, USA, 7-9 January 2016; pp. 39-46.

185. Klös, V.; Göthel, T.; Glesner, S. Comprehensible and dependable self-learning self-adaptive systems. *J. Syst. Archit.* **2018**, *85*, 28-42. [CrossRef]

186. Cámara, J.; Moreno, G.A.; Garlan, D. Stochastic game analysis and latency awareness for proactive self-adaptation. In Proceedings of the 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, Hyderabad, India, 2-3 June 2014; pp. 155-164.

187. Koh, Y.; Her, H.; Yi, K.; Kim, K. Integrated Speed and Steering Control Driver Model for Vehicle-Driver Closed-Loop Simulation. *IEEE Trans. Veh. Technol.* **2016**, *65*, 4401-4411. [CrossRef]

188. Li, J.; Zhang, Y.; Chen, Y. A Self-Adaptive Traffic Light Control System Based on Speed of Vehicles. In Proceedings of the 2016 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C), Vienna, Austria, 1-3 August 2016; pp. 382-388.

189. Perez-Palacin, D.; Mirandola, R. Uncertainties in the modeling of self-adaptive systems: A taxonomy and an example of availability evaluation. In Proceedings of the 5th ACM/SPEC International Conference on Performance Engineering, San Jose, CA, USA, 21 July 2014; pp. 3-14.

190. Esfahani, N.; Kouroshfar, E.; Malek, S. Taming uncertainty in self-adaptive software. In Proceedings of the 19th ACM SIGSOFT Symposium and the 13th European Conference on Foundations of Software Engineering, Szeged, Hungary, 5-9 September 2011; pp. 234-244.

191. Trapp, M.; Schneider, D. Safety assurance of open adaptive systems-a survey. In *Models@ Run. Time*; Springer: Berlin, Germany, 2014; pp. 279-318.

192. McGee, E.T.; McGregor, J.D. Using dynamic adaptive systems in safety-critical domains. In Proceedings of the 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, Austin, TX, USA, 16-17 May 2016; pp. 115-121.

193. Bozhinoski, D. Managing safety and adaptability in Mobile Multi-Robot systems. In Proceedings of the 11th International ACM SIGSOFT Conference on Quality of Software Architectures, Montréal, QC, Canada, 4-8 May 2015; pp. 135-140.
194. Klös, V.; Göthel, T.; Glesner, S. Formal Models for Analysing Dynamic Adaptation Behaviour in Real-Time Systems. In Proceedings of the IEEE International Workshops on Foundations and Applications of Self* Systems, Augsburg, Germany, 12–16 September 2016; pp. 106–111.

195. Zeller, M.; Prehofer, C. Timing constraints for runtime adaptation in real-time, networked embedded systems. In Proceedings of the 2012 ICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), Zürich, Switzerland, 4–5 June 2012; pp. 73–82.

196. Tan, L.; Du, C.; Dong, Y. Control-Performance-Driven Period and Deadline Selection for Cyber-Physical Systems. In Proceedings of the 2015 10th Asian Control Conference (ASCC), Kota Kinabalu, Malaysia, 31 May–3 June 2015.

197. Kim, J.; Kim, H.; Lakshmanan, K.; Rajkumar, R.R. Parallel scheduling for cyber-physical systems: Analysis and case study on a self-driving car. In Proceedings of the ACM/IEEE 4th International Conference on Cyber-Physical Systems, Philadelphia, PA, USA, 8–11 April 2013; pp. 31–40.

198. Kritikakou, A.; Marty, T.; Roy, M. DYNASCORE: DYNAmic Software COnroller to increase REsource utilization in mixed-critical systems. *ACM Trans. Des. Autom. Electron. Syst.* **2017**, *23*, 13. [CrossRef]

199. Wu, S.-y.; Zhang, P.; Li, F.; Gu, F.; Pan, Y. A hybrid discrete particle swarm optimization-genetic algorithm for multi-task scheduling problem in service oriented manufacturing systems. *J. Cent. South Univ.* **2016**, *23*, 421–429. [CrossRef]

200. Deb, K. Multi-objective optimization using evolutionary algorithms: An introduction. *Multi-Object. Evol. Optim. Prod. Des. Manuf.* **2011**, *1*, 24. [CrossRef]

201. Coello, C.C.; Dhaenens, C.; Jourdan, L. *Advances in Multi-Objective Nature Inspired Computing*; Springer: Berlin, Germany, 2009; Volume 272.

202. Zhang, K.; Zhang, D.; de La Fortelle, A.; Wu, X.; Grégoire, J. State-driven priority scheduling mechanisms for driverless vehicles approaching intersections. *IEEE Trans. Intell. Transp. Syst.* **2015**, *16*, 2487–2500. [CrossRef]

203. Bambagini, M.; Marinoni, M.; Aydin, H.; Buttazzo, G. Energy-Aware Scheduling for Real-Time Systems: A Survey. *ACM Trans. Embed. Comput. Syst.* **2016**, *15*, 7. [CrossRef]

204. Shepilov, Y.; Pavlova, D.; Kazanskaia, D. Multithreading MAS Platform for Real-Time Scheduling. *Int. J. Softw. Innov.* **2016**, *4*, 48–60. [CrossRef]

205. Jiang, J.-M.; Zhu, H.; Li, Q.; Zhao, Y.; Zhao, L.; Zhang, S.; Gong, P.; Hong, Z. Analyzing Event-Based Scheduling in Concurrent Reactive Systems. *ACM Trans. Embed. Comput. Syst.* **2015**, *14*, 86. [CrossRef]

206. Ruiz-Arenas, S.; Horváth, I.; Mejía-Gutiérrez, R.; Opiyo, E. Towards the maintenance principles of cyber-physical systems. *Stroj. Vestn. J. Mech. Eng.* **2014**, *60*, 815–831. [CrossRef]

207. Kans, M.; Galar, D.; Thaduri, A. Maintenance 4.0 in Railway Transportation Industry. In *A Data Fusion Approach of Multiple Maintenance Data Sources for Real-World Reliability Modelling*; Koskinen, K.T., Kortelainen, H., Aaltonen, J., Uusitalo, T., Komonen, K., Mathew, J., Laitinen, J., Eds.; Springer: Berlin/Heidelberg, Germany, 2016; pp. 317–331.

208. Bukowski, L. System of systems dependability—Theoretical models and applications examples. *Reliab. Eng. Syst. Saf.* **2016**, *151*, 76–92. [CrossRef]

209. Mittal, S.; Vetter, J.S. A survey of techniques for modeling and improving reliability of computing systems. *IEEE Trans. Parallel Distrib. Syst.* **2016**, *27*, 1226–1238. [CrossRef]

210. Cecati, C. A survey of fault diagnosis and fault-tolerant techniques—part II: Fault diagnosis with knowledge-based and hybrid/active approaches. *IEEE Trans. Ind. Electron.* **2015**, *62*, 3768–3774.

211. Muhammed, T.; Shaikh, R.A. An analysis of fault detection strategies in wireless sensor networks. *J. Netw. Comput. Appl.* **2017**, *78*, 267–287. [CrossRef]

212. Chouikhi, S.; El Korbi, I.; Ghamri-Doudane, Y.; Saidane, L.A. A survey on fault tolerance in small and large scale wireless sensor networks. *Comput. Commun.* **2015**, *69*, 22–37. [CrossRef]

213. Yang, W.; Liu, Y.; Xu, C.; Cheung, S.-C. A survey on dependability improvement techniques for pervasive computing systems. *Sci. China Inf. Sci.* **2015**, *58*, 1–14. [CrossRef]

214. Li, F.; Shi, P.; Wang, X.; Agarwal, R. Fault detection for networked control systems with quantization and Markovian packet dropouts. *Signal Process.* **2015**, *111*, 106–112. [CrossRef]

215. Xia, J.; Jiang, B.; Zhang, K.; Xu, J. Robust Fault Diagnosis Design for Linear Multiagent Systems with Incipient Faults. *Math. Probl. Eng.* **2015**, *2015*, 436935. [CrossRef]

216. Esfahani, P.M.; Lygeros, J. A tractable fault detection and isolation approach for nonlinear systems with probabilistic performance. *IEEE Trans. Autom. Control* **2016**, *61*, 633–647. [CrossRef]
217. Reppa, V.; Polycarpou, M.M.; Panayiotou, C.G. Distributed Sensor Fault Diagnosis for a Network of Interconnected Cyber-Physical Systems. *IEEE Trans. Control Netw. Syst.* **2015**, *2*, 11–23. [CrossRef]

218. Dong, H.; Wang, Z.; Ding, S.X.; Gao, H. A Survey on Distributed Filtering and Fault Detection for Sensor Networks. *Math. Probl. Eng.* **2014**, *2014*, 858624. [CrossRef]

219. Warriach, E.U.; Tei, K. Fault detection in wireless sensor networks: A machine learning approach. In Proceedings of the 2013 IEEE 16th International Conference on Computational Science and Engineering (CSE), Sydney, Australia, 3–5 December 2013; pp. 758–765.

220. Krishnamurthy, S.; Sarkar, S.; Tewari, A. Scalable anomaly detection and isolation in cyber-physical systems using bayesian networks. In Proceedings of the ASME 2014 Dynamic Systems and Control Conference, San Antonio, TX, USA, 22–24 October 2014; p. V002T26A006.

221. Sanislav, T.; Merza, K.; Mois, G.; Miclea, L. Cyber-physical system dependability enhancement through data mining. In Proceedings of the 2016 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR), Cluj-Napoca, Romania, 19–21 May 2016; pp. 1–5.

222. Khalid, Z.; Fisal, N.; Rozaini, M. A Survey of Middleware for Sensor and Network Virtualization. *Sensors* **2014**, *14*, 24046–24097. [CrossRef] [PubMed]

223. Zhou, P.; Zuo, D.-C.; Hou, K.-M.; Zhang, Z.; Shi, H.-L. A Light-weight Multilevel Recoverable Container for Event-driven System: A Self-healing CPS Approach. In Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016), Wuhan, China, 10–11 December 2016.

224. Ahn, S.; Yoo, C.; Lee, S.; Lee, H.; Kim, S.J. Implementing virtual platform for global-scale cyber physical system networks. *Int. J. Commun. Syst.* **2015**, *28*, 1899–1920. [CrossRef]

225. Khan, I.; Belqasmi, F.; Glitho, R.; Crespi, N.; Morrow, M.; Polakos, P. Wireless Sensor Network Virtualization: A Survey. *IEEE Commun. Surv. Tutor.* **2016**, *18*, 553–576. [CrossRef]

226. Dettoni, F.; Lung, L.C.; Luiz, A.F. Using Virtualization Technology for Fault-Tolerant Replication in LAN. In *New Results in Dependability and Computer Systems*; Zamojski, W., Mazurkiewicz, J., Sugier, J., Walkowiak, T., Kacprzyk, J., Eds.; Springer: Berlin/Heidelberg, Germany, 2013; Volume 224, pp. 131–140.

227. Quattrociocchi, W.; Caldarelli, G.; Scala, A. Self-Healing Networks: Redundancy and Structure. *PLoS ONE* **2014**, *9*, e87986. [CrossRef] [PubMed]

228. Hazra, A.; Dasgupta, P.; Chakrabarti, P.P. Formal assessment of reliability specifications in embedded cyber-physical systems. *J. Appl. Log.* **2016**, *18*, 71–104. [CrossRef]

229. Cui, Y.; Lane, J.; Voyles, R.; Krishnamoorthy, A. A new fault tolerance method for field robotics through a self-adaptation architecture. In Proceedings of the 2014 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), Hokkaido, Japan, 27–30 October 2014; pp. 1–6.

230. Warriach, E.U.; Ozcelebi, T.; Lukkien, J.J. Fault-prevention in smart environments for dependable applications. In Proceedings of the 2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems (SASO), Umea, Sweden, 8–12 September 2014; pp. 183–184.

231. Zheng, J.; Wang, P.; Li, C.; Mouftah, H.T. An Efficient Fault-Prevention Clustering Protocol for Robust Underwater Sensor Networks. In Proceedings of the IEEE International Conference on Communications (ICC’08), Beijing, China, 19–23 May 2008; pp. 2802–2807.

232. Cooray, D.; Kouroshfar, E.; Malek, S.; Roshandel, R. Proactive self-adaptation for improving the reliability of mission-critical, embedded, and mobile software. *IEEE Trans. Softw. Eng.* **2013**, *39*, 1714–1735. [CrossRef]

233. Yano, I.H.; Oliveira, V.C.; de Mello Fagotto, E.A.; Mota, A.D.A.; Mota, L.T.M. Predicting battery charge depletion in wireless sensor networks using received signal strength indicator. *J. Comput. Sci.* **2013**, *9*, 821–826. [CrossRef]

234. Warriach, E.U.; Ozcelebi, T.; Lukkien, J.J. A Comparison of Predictive Algorithms for Failure Prevention in Smart Environment Applications. In Proceedings of the 2015 International Conference on Intelligent Environments (IE), Prague, Czech Republic, 14 July 2015; pp. 33–40.

235. Németh, E.; Lakner, R.; Hangos, K.M.; Cameron, I.T. Prediction-based diagnosis and loss prevention using qualitative multi-scale models. *Inf. Sci.* **2007**, *177*, 1916–1930. [CrossRef]

236. Lakner, R.; Németh, E.; Hangos, K.M.; Cameron, I.T. Multiagent realization of prediction-based diagnosis and loss prevention. In Proceedings of the International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, Annecy, France, 27–30 June 2006; pp. 70–80.
237. Priesterjahn, C.; Steenken, D.; Tichy, M. Component-based timed hazard analysis of self-healing systems. In Proceedings of the 8th Workshop on Assurances for Self-Adaptive Systems, Szeged, Hungary, 4 September 2011; pp. 34–43.

238. Salfner, F.; Lenk, M.; Malek, M. A survey of online failure prediction methods. *ACM Comput. Surv.* **2010**, *42*, 10. [CrossRef]

239. Verma, A.K.; Srividya, A.; Ramesh, P. A systemic approach to integrated E-maintenance of large engineering plants. *Int. J. Autom. Comput.* **2010**, *7*, 173–179. [CrossRef]

240. Sleptchenko, A.; Johnson, M.E. Maintaining Secure and Reliable Distributed Control Systems. *Inf. J. Comput.* **2014**, *27*, 103–117. [CrossRef]

241. Wan, K.; Alagar, V. Achieving dependability of cyber physical systems with autonomic covering. In Proceedings of the 2014 IEEE 12th International Conference on Dependable, Autonomic and Secure Computing (DASC), Dalian, China, 24–27 August 2014; pp. 139–145.

242. Asplund, F. The future of software tool chain safety qualification. *Saf. Sci.* **2015**, *74*, 37–43. [CrossRef]

<figure><img src="image_20.png" /></figure>

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).