The cyber–physical system (CPS) combines computation, communication, control, and physical components to achieve common goals with minimal human intervention. CPS components can operate on various temporal and spatial scales, having different independent decision-making behavioral modalities and cooperating synchronously to reach a common goal. CPS includes Smart Cities, Smart Grid, Industrial IoT, Cloud Computing, and "Smart" Anything (e.g., Transportation Systems, Cars, Manufacturing, Hospitals, Homes, Supply-Chain Management, Appliances, etc.). The CPS components are expected to grow exponentially and will generate zettabytes of data in the near future due to indispensable advancements in artificial intelligence (AI), machine learning (ML), and optimization fields. CPSs demand innovative solutions for various challenging problems, i.e., Resource Provisioning, Trust Management Systems, Data Security & Privacy, Computation Offloading to Cloud Computing, Secure Communication, Swarm Robotics, and Automation, Medical Image Analysis, Object detection, Remote Sensing Image Segmentation, Unmanned Aerial Vehicle (UAV) Path Planning, Water Distribution Networks, Network Intrusion Detection, Text Clustering, Wind Turbine Placement Problem, Optimal Feature Selection in High-Dimensional Datasets, Genome Sequence Assembly, Designing Optimal Neural Networks, and many others. These problems demand intelligent techniques that are different from the traditional algorithms and capable of handling CPS's current and upcoming challenges.

Nature-inspired optimization algorithms are a class of metaheuristic algorithms for optimization that can solve complex real-world problems that are not efficiently solvable by traditional methods or whose models are too complex for mathematical reasoning. Nature-inspired optimization algorithms are inspired by natural phenomena and are scalable, adaptable, and sustainable. They can be categorized into four categories, i.e., Evolution, Swarm, Physics-based, and Immune-based, depending on the principles of natural evolution, collaborative behavior, laws of physics, and natural immune system, respectively. Nature-inspired algorithms can successfully solve many complex real-world problems in acceptable computational time. Hence, Nature-inspired Optimization algorithms with their variants can handle the complex issues of CPS and act accordingly to create better values in our daily lives.

Objectives, Impact, and Value

This book is the result of research by the teaching staff and research scholars of leading universities and contains the results of many years of scientific experiments and theoretical conclusions. The research works were tested, presented, discussed, and formed the basis of the book as a result of the online forum "Nature-Inspired Optimization Algorithms for Cyber-Physical Systems".

This book explores nature-inspired optimization algorithms intended to boost the performance of cyber-physical systems. It discusses and presents the critical challenges, opportunities, applications, and advancement of Nature-Inspired Optimization Algorithms for the complex problems of cyber-physical systems.

Target Audience and Potential Uses

This book interests the teaching staff, research scholars, and graduate students of leading higher educational institutions in computer science, AI & Machine Learning, nature-inspired optimization algorithms, and Cyber-Physical systems. The book will also be helpful to IT professionals, data scientists, and AI researchers.

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Editor/Author Biographies

Mohammad Sajid is an Assistant Professor in the Department of Computer Science, A.M.U. Aligarh, India. He has completed his M.C.A., M. Tech. and Ph.D. from School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi. Dr. MOHAMMAD SAJID has many research publications in different international conferences and international journals of repute. His research interests include Evolutionary Computation, Parallel Computing, Cloud Computing, and Internet of Things.

Dr. Mohammad Shahid is an Assistant Professor of Computer Science & Application in the Department of Commerce, A.M.U. Aligarh. He has completed his Ph.D. and M. Tech. from School of Computer and Systems Sciences, Jawaharlal Nehru University (JNU), New Delhi. He earned his M.C.A. from A.M.U. Aligarh. He has published 21 research papers with the publisher of international repute (including Elsevier, Inderscience, Online Wiley, Taylor & Francis, Emerald Insight, IGI Global etc.) and 15 book chapters in springer edited books. Also, he has published 15 research papers in the proceedings of online peer-reviewed International conferences indexed in Scopus. He is awarded with research startup grant (10 lakhs) from UGC-BSR (2017), India. one major research project (6 lakhs) from ICSSR, India, is sanctioned in 2020 under his principal investigation. He is reviewer of the journals from the publishers of international repute (such as Elsevier, Springer, etc.). He is also member of IEEE.

Maria Lapina is an accomplished professional in academia and international affairs, currently serving as Vice Director for International Affairs and Associate Professor in the Department of Information Security of Automated Systems. She holds a PhD in Mathematics with honors from Stavropol State University, defended in 2005, and achieved the academic degree of Associate Professor in 2009. Maria also holds a Master's degree in Information Security with honors from North Caucasian Federal University, obtained in 2015. Her commitment to continuous learning is evident through her completion of professional retraining in "Software Development and Data Analysis" at St. Petersburg State University in 2020. Maria has participated in international internships at the University of Rome Sapienza (Italy), University of Ljubljana (Slovenia), Technical University of Dresden (Germany), and the 2nd ASEF Higher Education Innovation Laboratory (ASEFInnoLab) at Fudan University in Shanghai, China. Her dedication to academia and international collaboration highlights her passion for advancing knowledge and fostering global partnerships in Information Security.

MIKHAIL BABENKO graduated in mathematics from Stavropol State University (SSU), in 2007, and the Ph.D. degree in mathematics from SSU, in 2011. He is currently the Head of the Department of Computational Mathematics and Cybernetics with North-Caucasus Federal University. He is the author of over 77 publications and five patents. His research interests include cloud computing, high-performance computing, residue number systems, neural networks, and cryptography.

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