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Author: Shreevatsa Rajagopalan
Publisher:
ISBN:
Category :
Languages : en
Pages : 40
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Book Description
The question of computing average of numbers present at nodes in a network in a distributed manner using gossip or message-passing algorithms has been of great recent interest across disciplines -- algorithms, control and robotics, estimation, social networks, etc. It has served as a non-trivial, representative model for an important class of questions arising in these disciplines and thus guiding intellectual progress over the past few decades. In most of these applications, there is inherent dynamics present, such as changes in the network topology in terms of communication links, changes in the values of numbers present at nodes, and nodes joining or leaving. The effect of dynamics in terms of communication links on the design and analysis of algorithms for averaging is reasonably well understood, e.g. [14][2][8][4]. However, little is known about the effect of other forms of dynamics. In this thesis, we study the effect of such types of dynamics in the context of maintaining average in the network. Specifically, we design dynamics-aware message-passing or gossip algorithm that maintains good estimate of average in presence of continuous change in numbers at nodes. Clearly, in presence of such dynamics the best one can hope for is a tradeoff between the accuracy of each node's estimate of the average at each time instant and the rate of dynamics. For our algorithm, we characterize this tradeoff and establish it to be near optimal. The dependence of the accuracy of the algorithm on the rate of dynamics as well as on the underlying graph structure is quantified.
Author: Shreevatsa Rajagopalan
Publisher:
ISBN:
Category :
Languages : en
Pages : 40
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Book Description
The question of computing average of numbers present at nodes in a network in a distributed manner using gossip or message-passing algorithms has been of great recent interest across disciplines -- algorithms, control and robotics, estimation, social networks, etc. It has served as a non-trivial, representative model for an important class of questions arising in these disciplines and thus guiding intellectual progress over the past few decades. In most of these applications, there is inherent dynamics present, such as changes in the network topology in terms of communication links, changes in the values of numbers present at nodes, and nodes joining or leaving. The effect of dynamics in terms of communication links on the design and analysis of algorithms for averaging is reasonably well understood, e.g. [14][2][8][4]. However, little is known about the effect of other forms of dynamics. In this thesis, we study the effect of such types of dynamics in the context of maintaining average in the network. Specifically, we design dynamics-aware message-passing or gossip algorithm that maintains good estimate of average in presence of continuous change in numbers at nodes. Clearly, in presence of such dynamics the best one can hope for is a tradeoff between the accuracy of each node's estimate of the average at each time instant and the rate of dynamics. For our algorithm, we characterize this tradeoff and establish it to be near optimal. The dependence of the accuracy of the algorithm on the rate of dynamics as well as on the underlying graph structure is quantified.
Author: Adel Aghajan Abdollah
Publisher:
ISBN:
Category :
Languages : en
Pages : 140
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Book Description
In this thesis, we study Distributed Averaging Dynamics and its main application, i.e. Distributed Optimization. More specifically, the results of this thesis can be divided into two main parts: 1) Ergodicity of distributed averaging dynamics, and 2) Distributed optimization over dependent random networks. First, we study both discrete-time and continuous-time time-varying distributed averaging dynamics. We show a necessary and a sufficient condition for ergodicity of such dynamics. We extend a well-known result in ergodicity of time-homogeneous (time-invariant) averaging dynamics and we show that ergodicity of a dynamics necessitates that its (directed) infinite flow graph has a spanning rooted tree. Then, we show that if groups of agents are connected using a rooted tree and the averaging dynamics restricted to each group is P* and ergodic, then the dynamics over the whole networks is ergodic. In particular, this provides a general condition for convergence of consensus dynamics where groups of agents capable of reaching consensus follow each other on a time-varying network. Then, we study the averaging-based distributed optimization solvers over random networks for both convex and strongly convex functions. We show a general result on the convergence of such schemes for a broad class of dependent weight-matrix sequences. In addition to implying many of the previously known results on this domain, our work shows the robustness of distributed optimization results to link-failure. Also, it provides a new tool for synthesizing distributed optimization algorithms. To prove our main theorems, we establish new results on the rate of convergence analysis of averaging dynamics and non-averaging dynamics over (dependent) random networks. These secondary results, along with the required martingale-type results to establish them, might be of interest to broader research endeavors in distributed computation over random networks.
Author: Behrouz Touri
Publisher: Springer Science & Business Media
ISBN: 364228003X
Category : Technology & Engineering
Languages : en
Pages : 152
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Book Description
The thesis deals with averaging dynamics in a multiagent networked system, which is a main mechanism for diffusing the information over such networks. It arises in a wide range of applications in engineered physical networks (such as mobile communication and sensor networks), as well as social and economic networks. The thesis provides in depth study of stability and other phenomena characterizing the limiting behavior of both deterministic and random averaging dynamics. By developing new concepts, and using the tools from dynamic system theory and non-negative matrix theory, several novel fundamental results are rigorously developed. These contribute significantly to our understanding of averaging dynamics as well as to non-negative random matrix theory. The exposition, although highly rigorous and technical, is elegant and insightful, and accompanied with numerous illustrative examples, which makes this thesis work easily accessible to those just entering this field and will also be much appreciated by experts in the field.
Author: Angelia Nedić
Publisher:
ISBN: 9781680830408
Category : Computers
Languages : en
Pages : 116
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Book Description
This is the first tutorial to give such a concise and accessible introduction to game theory. It will be of use to all students, practitioners, and researchers looking to understand the basic concepts, models, and applications.
Author: Fei Chen
Publisher: Springer Nature
ISBN: 3030395367
Category : Technology & Engineering
Languages : en
Pages : 240
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Book Description
This book presents a systematic study of an emerging field in the development of multi-agent systems. In a wide spectrum of applications, it is now common to see that multiple agents work cooperatively to accomplish a complex task. The book assists the implementation of such applications by promoting the ability of multi-agent systems to track — using local communication only — the mean value of signals of interest, even when these change rapidly with time and when no individual agent has direct access to the average signal across the whole team; for example, when a better estimation/control performance of multi-robot systems has to be guaranteed, it is desirable for each robot to compute or track the averaged changing measurements of all the robots at any time by communicating with only local neighboring robots. The book covers three factors in successful distributed average tracking: algorithm design via nonsmooth and extended PI control; distributed average tracking for double-integrator, general-linear, Euler–Lagrange, and input-saturated dynamics; and applications in dynamic region-following formation control and distributed convex optimization. The book presents both the theory and applications in a general but self-contained manner, making it easy to follow for newcomers to the topic. The content presented fosters research advances in distributed average tracking and inspires future research directions in the field in academia and industry.
Author: Fabio Fagnani
Publisher: Springer
ISBN: 3319680226
Category : Technology & Engineering
Languages : en
Pages : 145
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Book Description
This book deals with averaging dynamics, a paradigmatic example of network based dynamics in multi-agent systems. The book presents all the fundamental results on linear averaging dynamics, proposing a unified and updated viewpoint of many models and convergence results scattered in the literature. Starting from the classical evolution of the powers of a fixed stochastic matrix, the text then considers more general evolutions of products of a sequence of stochastic matrices, either deterministic or randomized. The theory needed for a full understanding of the models is constructed without assuming any knowledge of Markov chains or Perron–Frobenius theory. Jointly with their analysis of the convergence of averaging dynamics, the authors derive the properties of stochastic matrices. These properties are related to the topological structure of the associated graph, which, in the book’s perspective, represents the communication between agents. Special attention is paid to how these properties scale as the network grows in size. Finally, the understanding of stochastic matrices is applied to the study of other problems in multi-agent coordination: averaging with stubborn agents and estimation from relative measurements. The dynamics described in the book find application in the study of opinion dynamics in social networks, of information fusion in sensor networks, and of the collective motion of animal groups and teams of unmanned vehicles. Introduction to Averaging Dynamics over Networks will be of material interest to researchers in systems and control studying coordinated or distributed control, networked systems or multiagent systems and to graduate students pursuing courses in these areas.
Author: Christoforos N. Hadjicostis
Publisher: Foundations and Trends (R) in Systems and Control
ISBN: 9781680834383
Category : Automatic control
Languages : en
Pages : 208
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Book Description
The emergence of complex systems that are controlled over wireless and wired broadband networks, ranging from smart grids and traffic networks to embedded electronic devices and robotic networks, has sparked huge interest in distributed control problems. This is due to the need to properly coordinate the information exchange between sensors, actuators, and controllers in order to enforce a desirable behavior, without relying on a centralized decision maker. This monograph focuses on the key operations of distributed average consensus and weight/flow balancing under a variety of communication topologies and adversarial network conditions such as delays and packet drops. Divided into two parts, Theory and Applications, it first provides the reader with thorough grounding into the theory underpinning the research before discussing two applications in detail. Namely, the coordination of distributed energy resources and the computation of PageRank values. The monograph will be of interest to all researchers, students and practitioners working control, coordination, and optimization tasks in many emerging networked applications.
Author: Seyed Rasoul Etesami
Publisher: Springer
ISBN: 3319542893
Category : Technology & Engineering
Languages : en
Pages : 190
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Book Description
This work makes major contributions to the thriving area of social, communication, and distributed networks by introducing novel methodologies and tools toward the study of the evolutionary behaviors of these networks, as well as their computational complexity and rates of convergence. By departing from the classical approaches and results in the literature, this work shows that it is possible to handle more complex and realistic nonlinear models where either the traditional approaches fail or lead to weak results. The author also develops several easily implementable algorithms, delivering excellent performance guarantees while running faster than those that exist in the literature. The study undertaken and the approaches adopted enable the analysis of the evolution of several different types of social and distributed networks, with the potential to apply to and resolve several other outstanding issues in such networks.
Author: Bernhard Ø. Palsson
Publisher: Cambridge University Press
ISBN: 1139495429
Category : Science
Languages : en
Pages : 333
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Book Description
Biophysical models have been used in biology for decades, but they have been limited in scope and size. In this book, Bernhard Ø. Palsson shows how network reconstructions that are based on genomic and bibliomic data, and take the form of established stoichiometric matrices, can be converted into dynamic models using metabolomic and fluxomic data. The Mass Action Stoichiometric Simulation (MASS) procedure can be used for any cellular process for which data is available and allows a scalable step-by-step approach to the practical construction of network models. Specifically, it can treat integrated processes that need explicit accounting of small molecules and protein, which allows simulation at the molecular level. The material has been class-tested by the author at both the undergraduate and graduate level. All computations in the text are available online in MATLAB® and Mathematica® workbooks, allowing hands-on practice with the material.
Author: Magdi S. Mahmoud
Publisher: Academic Press
ISBN: 012823203X
Category : Technology & Engineering
Languages : en
Pages : 396
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Book Description
Advanced Distributed Consensus for Multiagent Systems contributes to the further development of advanced distributed consensus methods for different classes of multiagent methods. The book expands the field of coordinated multiagent dynamic systems, including discussions on swarms, multi-vehicle and swarm robotics. In addition, it addresses advanced distributed methods for the important topic of multiagent systems, with a goal of providing a high-level treatment of consensus to different versions while preserving systematic analysis of the material and providing an accounting to math development in a unified way. This book is suitable for graduate courses in electrical, mechanical and computer science departments. Consensus control in multiagent systems is becoming increasingly popular among researchers due to its applicability in analyzing and designing coordination behaviors among agents in multiagent frameworks. Multiagent systems have been a fascinating subject amongst researchers as their practical applications span multiple fields ranging from robotics, control theory, systems biology, evolutionary biology, power systems, social and political systems to mention a few. Gathers together the theoretical preliminaries and fundamental issues related to multiagent systems and controls Provides coherent results on adopting a multiagent framework for critically examining problems in smart microgrid systems Presents advanced analysis of multiagent systems under cyberphysical attacks and develops resilient control strategies to guarantee safe operation
