Distributed Optimization for Smart Cyber-Physical Networks

Distributed Optimization for Smart Cyber-Physical Networks
Author: GIUSEPPE NOTARSTEFANO;IVANO NOTARNICOLA;ANDREA CAM.
Publisher:
Total Pages: 139
Release: 2019
Genre: Cooperating objects (Computer systems)
ISBN: 9781680836196

Distributed Optimization for Smart Cyber-Physical Networks provides the reader with an accessible overview of the current research and gives important pointers towards new developments. It is an excellent starting point for research and students unfamiliar with the topic.

Distributed Optimization for Smart Cyber-Physical Networks

Distributed Optimization for Smart Cyber-Physical Networks
Author: Giuseppe Notarstefano
Publisher:
Total Pages: 148
Release: 2019-12-11
Genre: Technology & Engineering
ISBN: 9781680836189

In an increasingly connected world, the term cyber-physical networks has been coined to refer to the communication among devices that is turning smart devices into smart (cooperating) systems. The distinctive feature of such systems is that significant advantage can be obtained if its interconnected, complex nature is exploited. Several challenges arising in cyber-physical networks can be stated as optimization problems. Examples are estimation, decision, learning and control applications. In cyber-physical networks, the goal is to design algorithms, based on the exchange of information among the processors, that take advantage of the aggregated computational power. Distributed Optimization for Smart Cyber-Physical Networks provides a comprehensive overview of the most common approaches used to design distributed optimization algorithms, together with the theoretical analysis of the main schemes in their basic version. It identifies and formalizes classes of problem set-ups that arise in motivating application scenarios. For each set-up, in order to give the main tools for analysis, tailored distributed algorithms in simplified cases are reviewed. Extensions and generalizations of the basic schemes are also discussed at the end of each chapter. Distributed Optimization for Smart Cyber-Physical Networks provides the reader with an accessible overview of the current research and gives important pointers towards new developments. It is an excellent starting point for research and students unfamiliar with the topic.

Optimizing Control of Distributed Cyber-Physical Systems

Optimizing Control of Distributed Cyber-Physical Systems
Author: Zonglin Liu
Publisher: BoD – Books on Demand
Total Pages: 178
Release: 2021-01-01
Genre: Technology & Engineering
ISBN: 3737609764

In this thesis, a set of modeling and control strategies are proposed for Cyberphysical systems (CPS), which aim at ensuring a safe, reliable, and highly performant operation of each local subsystem contained in the CPS. Modeling of CPS is challenging since not only must the tight interconnection of continuous and discrete dynamics of local subsystems be exactly represented, but so must also the interleaving structure between different subsystems. Optimal control of CPS, accordingly, should take into account not only the local mixed dynamics by local controller synthesis, but also the influence from other subsystems around.

Distributed Optimization: Advances in Theories, Methods, and Applications

Distributed Optimization: Advances in Theories, Methods, and Applications
Author: Huaqing Li
Publisher: Springer Nature
Total Pages: 243
Release: 2020-08-04
Genre: Technology & Engineering
ISBN: 9811561095

This book offers a valuable reference guide for researchers in distributed optimization and for senior undergraduate and graduate students alike. Focusing on the natures and functions of agents, communication networks and algorithms in the context of distributed optimization for networked control systems, this book introduces readers to the background of distributed optimization; recent developments in distributed algorithms for various types of underlying communication networks; the implementation of computation-efficient and communication-efficient strategies in the execution of distributed algorithms; and the frameworks of convergence analysis and performance evaluation. On this basis, the book then thoroughly studies 1) distributed constrained optimization and the random sleep scheme, from an agent perspective; 2) asynchronous broadcast-based algorithms, event-triggered communication, quantized communication, unbalanced directed networks, and time-varying networks, from a communication network perspective; and 3) accelerated algorithms and stochastic gradient algorithms, from an algorithm perspective. Finally, the applications of distributed optimization in large-scale statistical learning, wireless sensor networks, and for optimal energy management in smart grids are discussed.

Cyber-Physical Distributed Systems

Cyber-Physical Distributed Systems
Author: Giovanni Sansavini
Publisher: John Wiley & Sons
Total Pages: 224
Release: 2021-08-11
Genre: Technology & Engineering
ISBN: 1119682711

CYBER-PHYSICAL DISTRIBUTED SYSTEMS Gather detailed knowledge and insights into cyber-physical systems behaviors from a cutting-edge reference written by leading voices in the field In Cyber-Physical Distributed Systems: Modeling, Reliability Analysis and Applications, 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. The 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. Cyber-Physical Distributed Systems covers recent advances in combinatorial models and algorithms for cyber-physical systems modeling and analysis. The book also includes: A 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 Discussions of general modeling, assessment, verification, and optimization of industrial cyber-physical systems Explorations of stability analysis and enhancement of cyber-physical systems, including the integration of physical systems and open communication networks A detailed treatment of a system-of-systems framework for the reliability analysis and optimal maintenance of distributed systems with aging components Perfect for undergraduate and graduate students in computer science, electrical engineering, cyber security, industrial and system engineering departments, Cyber-Physical Distributed Systems 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.

Multilayer Control of Networked Cyber-Physical Systems

Multilayer Control of Networked Cyber-Physical Systems
Author: Sabato Manfredi
Publisher: Springer
Total Pages: 153
Release: 2016-09-17
Genre: Technology & Engineering
ISBN: 3319416464

This book faces the interdisciplinary challenge of formulating performance-assessing design approaches for networked cyber-physical systems (NCPSs). Its novel distributed multilayer cooperative control deals simultaneously with communication-network and control performance required for the network and application layers of an NCPS respectively. Practically, it distributes the computational burden among different devices, which act cooperatively to achieve NCPS goals. The approach can be applied to NCPSs based on both wired and wireless technologies and so is suitable for future network infrastructures in which different protocols and technologies coexist. The book reports realistic results from performance evaluation of the new approach, when applied in different operative scenarios. Readers of this book will benefit by: learning a general, technology-independent methodology for the design and implementation of cooperative distributed algorithms for flow control at the network layer of an NCPS that gives algorithm-parameter-tuning guidelines for assessing the desired quality of service performance; learning a general methodology for the design and implementation of consensus-based algorithms at the application layer that allows monitoring and control of distributed physical systems and gives algorithm-parameter-tuning guidelines for assessing the desired control system performance; understanding the main network simulators needed to validate the effectiveness of the proposed multilayer control approach in different realistic network operation scenarios; and practising with a cooperative multilayer control project that assesses acceptable NCPS performance in networked monitoring and robot systems, autonomous and queuing networks, and other critical human relief applications. Researchers, graduate students and practitioners working in automation, engineering, sensor networks, mobile robotics and computer networks will find this book instructive. It will also be helpful to network administrators and technicians implementing application-layer and network-layer solutions or installing, configuring or troubleshooting network and control system components of NCPSs.

Convergence Rate of Distributed Averaging Dynamics and Optimization in Networks

Convergence Rate of Distributed Averaging Dynamics and Optimization in Networks
Author: Angelia Nedić
Publisher:
Total Pages: 100
Release: 2015
Genre: Computer networks
ISBN: 9781680830415

Recent advances in wired and wireless technology lead to the emergence of large-scale networks such as Internet, wireless mobile ad-hoc networks, swarm robotics, smart-grid, and smart-sensor networks. The advances gave rise to new applications in networks including decentralized resource allocation in multi-agent systems, decentralized control of multi-agent systems, collaborative decision making, decentralized learning and estimation, and decentralized in-network signal processing. The advances also gave birth to new large cyber-physical systems such as sensor and social networks. These network systems are typically spatially distributed over a large area and may consists of hundreds of agents in smart-sensor networks to millions of agents in social networks. As such, they do not possess a central coordinator or a central point for access to the complete system information. This lack of central entity makes the traditional (centralized) optimization and control techniques inapplicable, thus necessitating the development of new distributed computational models and algorithms to support efficient operations over such networks. This tutorial provides an overview of the convergence rate of distributed algorithms for coordination and its relevance to optimization in a system of autonomous agents embedded in a communication network, where each agent is aware of (and can communicate with) its local neighbors only. The focus is on distributed averaging dynamics for consensus problems and its role in consensus-based gradient methods for convex optimization problems, where the network objective function is separable across the constituent agents.

Optimization, Learning, and Control for Interdependent Complex Networks

Optimization, Learning, and Control for Interdependent Complex Networks
Author: M. Hadi Amini
Publisher: Springer Nature
Total Pages: 306
Release: 2020-02-22
Genre: Technology & Engineering
ISBN: 3030340945

This book focuses on a wide range of optimization, learning, and control algorithms for interdependent complex networks and their role in smart cities operation, smart energy systems, and intelligent transportation networks. It paves the way for researchers working on optimization, learning, and control spread over the fields of computer science, operation research, electrical engineering, civil engineering, and system engineering. This book also covers optimization algorithms for large-scale problems from theoretical foundations to real-world applications, learning-based methods to enable intelligence in smart cities, and control techniques to deal with the optimal and robust operation of complex systems. It further introduces novel algorithms for data analytics in large-scale interdependent complex networks. • Specifies the importance of efficient theoretical optimization and learning methods in dealing with emerging problems in the context of interdependent networks • Provides a comprehensive investigation of advance data analytics and machine learning algorithms for large-scale complex networks • Presents basics and mathematical foundations needed to enable efficient decision making and intelligence in interdependent complex networks M. Hadi Amini is an Assistant Professor at the School of Computing and Information Sciences at Florida International University (FIU). He is also the founding director of Sustainability, Optimization, and Learning for InterDependent networks laboratory (solid lab). He received his Ph.D. and M.Sc. from Carnegie Mellon University in 2019 and 2015 respectively. He also holds a doctoral degree in Computer Science and Technology. Prior to that, he received M.Sc. from Tarbiat Modares University in 2013, and the B.Sc. from Sharif University of Technology in 2011.

Distributed Optimization-Based Control of Multi-Agent Networks in Complex Environments

Distributed Optimization-Based Control of Multi-Agent Networks in Complex Environments
Author: Minghui Zhu
Publisher: Springer
Total Pages: 133
Release: 2015-06-11
Genre: Technology & Engineering
ISBN: 3319190725

This book offers a concise and in-depth exposition of specific algorithmic solutions for distributed optimization based control of multi-agent networks and their performance analysis. It synthesizes and analyzes distributed strategies for three collaborative tasks: distributed cooperative optimization, mobile sensor deployment and multi-vehicle formation control. The book integrates miscellaneous ideas and tools from dynamic systems, control theory, graph theory, optimization, game theory and Markov chains to address the particular challenges introduced by such complexities in the environment as topological dynamics, environmental uncertainties, and potential cyber-attack by human adversaries. The book is written for first- or second-year graduate students in a variety of engineering disciplines, including control, robotics, decision-making, optimization and algorithms and with backgrounds in aerospace engineering, computer science, electrical engineering, mechanical engineering and operations research. Researchers in these areas may also find the book useful as a reference.