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distributed averaging in Sensor Networks Based on Broadcast Gossip Algorithms

IEEE SENSORS JOURNAL 2011年第3期11卷 808-817页

作者： Franceschelli, Mauro Giua, Alessandro Seatzu, Carla Univ Cagliari Dept Elect & Elect Engn I-09123 Cagliari Italy

In this paper, we propose a new decentralized algorithm to solve the consensus on the average problem on sensor networks through a gossip algorithm based on broadcasts. We directly extend previous results by not requiring that the digraph representing the network topology be balanced. Our algorithm is an improvement with respect to known gossip algorithms based on broadcasts in that the average of the initial state is preserved after each broadcast. The nodes are assumed to know their out-degree anytime they transmit information.

关键词： Consensus distributed averaging gossip algorithms sensor networks

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distributed averaging Under Constraints on Information Exchange: Emergence of Levy Flights

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2012年第10期57卷 2435-2449页

作者： Wang, Jing Elia, Nicola Iowa State Univ Dept Elect & Comp Engn Ames IA 50010 USA

In this paper, we study the fragility of a popular distributed averaging algorithm when the information exchange among the nodes is limited by communication delays, fading connections and additive noise. We show that the otherwise well studied and benign multi-agent system can generate a collective global complex behavior. We characterize this behavior, common to many natural and human-made interconnected systems, as a collective hyper-jump diffusion process and as a Levy flight process in a special case. We further describe the mechanism for its emergence and predict its occurrence, under standard assumptions, by checking the Mean Square instability of a certain part of the system. We show that the strong connectivity property of the network topology guarantees that the complex behavior is global and manifested by all the agents in the network, even though the source of uncertainty is localized. This work is the first, to the best of our knowledge, to establish the intimate relationship between the propagation of channel uncertainties in networked systems, the MS stability robustness and the emergence of Levy flights in distributed averaging systems. As averaging is central to science and engineering, the results of the paper may have far-reaching consequences on the understanding and engineering of complex networked systems.

关键词： Complex systems distributed averaging distributed consensus hyper-jump diffusion processes Levy flights mean square stability networked systems

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distributed averaging Algorithms Resilient to Communication Noise and Dropouts

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2013年第9期61卷 2231-2242页

作者： Wang, Jing Elia, Nicola Iowa State Univ Dept Elect & Comp Engn Ames IA 50011 USA

In this paper, we consider the problem of distributed average computation over communication networks whose channels are non-ideal, but noisy and/or intermittent. Channel intermittency captures randomness of network interconnections and packet-drop links. Based on input-output properties of feedback systems, we propose novel iterative algorithms that incorporate a networked feedback compensator to mitigate effects of the unreliable communication on distributed averaging. The new algorithms are time-invariant and do not suffer from the random walk behavior to additive noise of other average consensus algorithms. Moreover, the use of the link state information at the receiver leads to a new algorithm, which computes averages approximately correctly in the presence of intermittent communication and additive noise, under certain conditions.

关键词： Additive noise distributed averaging link failures mean square stability random networks

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distributed averaging With Random Network Graphs and Noises

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IEEE TRANSACTIONS ON INFORMATION THEORY 2018年第11期64卷 7063-7080页

作者： Li, Tao Wang, Jiexiang East China Normal Univ Sch Math Sci Key Lab Pure Math & Math Practice Shanghai 200241 Peoples R China Shanghai Univ Sch Mechatron Engn & Automat Shanghai 200072 Peoples R China

We consider a discrete-time distributed averaging algorithm over multi-agent networks with measurement noises and time-varying random graphs. Each agent updates its state by a weighted sum of pairwise state differences between its neighbors and itself with both additive and multiplicative measurement noises. The network structure is modeled by a sequence of time-varying random digraphs, which may be spatially and temporally dependent. By stochastic Lyapunov method and the combination of algebraic graph theory and martingale convergence theory, we obtain sufficient conditions for stochastic approximation type algorithms to achieve mean square and almost sure average consensus. We prove that all states of the agents converge to a common random variable, whose mathematical expectation is the average of initial values, in mean square and almost surely if the sequence of digraphs is conditionally balanced and uniformly conditionally jointly connected. An upper bound of the variance of the limit random variable, that is, the mean square steady-state error for stochastic average consensus is given quantitatively related to the weights, the algorithm gain and the energy level of the noises.

关键词： distributed averaging multi-agent system additive and multiplicative noise time-varying random graph

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distributed averaging with linear objective maps

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AUTOMATICA 2016年 70卷 179-188页

作者： Chen, Xudong Belabbas, Mohamed-Ali Basar, Tamer Univ Illinois Coordinated Sci Lab Champaign IL 61820 USA Univ Illinois Dept Elect & Comp Engn Champaign IL USA

A distributed averaging system is a linear multi-agent system in which agents communicate to reach an agreement (or a consensus) state, defined as the average of the initial states of the agents. Consider a more generalized situation in which each agent is given a nonnegative weight and the agreement state is defined as the weighted average of the initial conditions. We characterize in this paper the weighted averages that can be evaluated in a decentralized way by agents communicating over a directed graph. Specifically, we introduce a linear function, called the objective map, that defines the desired final state as a function of the initial states of the agents. We then provide a complete answer to the question of whether there is a decentralized consensus dynamics over a given digraph which converges to the final state specified by an objective map. In particular, we characterize not only the set of objective maps that are feasible for a given digraph, but also the consensus dynamics that implements the objective map. In addition, we present a decentralized algorithm to design the consensus dynamics. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Networked control systems Multi-agent systems Decentralized systems distributed averaging

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distributed averaging Problems Over Directed Signed Networks

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2021年第3期8卷 1442-1453页

作者： Du, Mingjun Meng, Deyuan Wu, Zheng-Guang Qilu Univ Technol Shandong Acad Sci Sch Elect Engn & Automat Jinan 250353 Peoples R China Beihang Univ BUAA Res Div 7 Beijing 100191 Peoples R China Beihang Univ BUAA Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China Zhejiang Univ Inst Cyber Syst & Control Natl Lab Ind Control Technol Hangzhou 310027 Peoples R China

This article aims at addressing distributed averaging problems for signed networks in the presence of general directed topologies that are represented by signed digraphs. A new class of improved Laplacian potential functions is proposed by presenting two notions of any signed digraph: induced unsigned digraph and mirror (undirected) signed graph, based on which two distributed averaging protocols are designed using the nearest neighbor rules. It is shown that with any of the designed protocols, signed-average consensus (respectively, state stability) can be achieved if and only if the associated signed digraph of signed network is structurally balanced (respectively, unbalanced), regardless of whether weight balance is satisfied or not. Further, improved Laplacian potential functions can be exploited to solve fixed-time consensus problems of signed networks with directed topologies, in which a non-linear distributed protocol is proposed to ensure the bipartite consensus or state stability within a fixed time. Additionally, the convergence analyses of directed signed networks can be implemented with the Lyapunov stability analysis method, which is realized by revealing the tight relationship between convergence behaviors of directed signed networks and properties of improved Laplacian potential functions. Simulation examples are presented to demonstrate the validity of our theoretical results for directed signed networks.

关键词： Directed topology distributed averaging fixed-time consensus signed-average consensus signed network

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distributed averaging Control for Voltage Regulation and Current Sharing in DC Microgrids: Modelling and Experimental Validation

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IFAC-PapersOnLine 2018年第23期51卷 242-247页

作者： Trip, Sebastian Han, Renke Cucuzzella, Michele Cheng, Xiaodong Scherpen, Jacquelien Guerrero, Josep Jan C. Willems Center for Systems and Control ENTEG Faculty of Mathematics and Natural Sciences University of Groningen Nijenborgh 4 GroningenAG9747 Netherlands Department of Energy Technology Aalborg University Pontoppidanstræde 111 Aalborg9220 Denmark

In this paper we study a distributed control scheme, achieving current sharing and average voltage regulation in Direct Current (DC) microgrids. The considered DC microgrid is composed of several distributed Generation Units (DGUs) interconnected, through resistive-inductive power lines, with loads. Each DGU includes a generic energy source that supplies the loads through a DC-DC buck converter. Remarkably, the proposed control scheme achieves average voltage regulation without the need of voltage measurements. An experimental validation is performed to assess the capabilities of the solution in a real network. The initial results are promising and show an additional need to compensate for partly unknown resistances present at the DGUs. © 2018

关键词： DC-DC converters Voltage regulators Control schemes Dc microgrids DC DC buck converter distributed averaging distributed control distributed control schemes distributed generation units Experimental validations

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distributed averaging Using Compensation

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IEEE COMMUNICATIONS LETTERS 2013年第8期17卷 1672-1675页

作者： Mou, Shaoshuai Cao, Ming Yale Univ Dept Elect Engn New Haven CT 06520 USA Univ Groningen Fac Math & Nat Sci ITM NL-9700 AB Groningen Netherlands

In a sensor network of n nodes, each node i is assigned with a time-dependent scalar state x(i)(t) and is able to exchange information with a certain number of other nodes called its neighbor nodes. The distributed averaging algorithm is to drive each x(i)(t), 1 <= i <= n, to converge to 1/n Sigma(n)(i-1) x(i)(0), the average of the initial state values of all nodes, only by communication between each node and its neighbor nodes. This paper proposes a new request-based distributed averaging protocol using the idea of compensation, in which at each time t each node i first updates its state to a weighted average of its own current state x(i)(t) and the current states of some neighbor nodes and then compensates its updated value by the change in the sums, before and after the update, of the states of all the nodes involved. It is proved that the proposed protocol drives all the x(i)(t) to converge to 1/n Sigma(n)(i=1) x(i)(0). Simulations on random networks are also provided to show that this new protocol converges much faster and consumes less energy than the deterministic gossiping protocol in [1].

关键词： Compensation distributed averaging networks

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distributed averaging in Opinion Dynamics 23

Distributed Averaging in Opinion Dynamics

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42nd ACM SIGACT-SIGOPS Symposium on Principles of distributed Computing (PODC)

作者： Berenbrink, P. Cooper, C. Gava, C. Mallmann-Trenn, F. Radzik, T. Marzagao, D. Kohan Rivera, N. Univ Hamburg Hamburg Germany Kings Coll London London England Univ Oxford Oxford England Univ Valparaiso Valparaiso Chile

ISBN: (纸本)9798400701214

We consider two simple asynchronous opinion dynamics on arbitrary graphs where every node u of the graph has an initial value xi(u)(0). In the first process, which we call the Nodemodel, at each time step t >= 0, a random node.. and a random sample of k of its neighbours v(1), v(2), . . . , v(k) are selected. Then, u updates its current value xi(u)(t) to xi(u)(t + 1) = alpha xi(u) (t) + (1-alpha)/k Sigma(k)(i-1) xi(vi)(t), where alpha is an element of(0, 1) and k >= 1 are parameters of the process. In the second process, called the. Edgemodel, at each step a random pair of adjacent nodes (u , v) is selected, and then nodeu updates its value equivalently to the Nodemodel with k = 1 and v as the selected neighbour. For both processes, the values of all nodes converge to the same value F, which is a random variable depending on the random choices made in each step. For the Nodemodel and regular graphs, and for the Edgemodel and arbitrary graphs, the expectation of F is the average of the initial values 1/n Sigma(u is an element of V) xi(u)(0). For the Nodemodel and non-regular graphs, the expectation of F is the degree-weighted average of the initial values. Our results are two-fold. We consider the concentration of F and show tight bounds on the variance of F for regular graphs. We show that when the initial values do not depend on the number of nodes, then the variance is negligible, and hence the nodes are able to estimate the initial average of the node values. Interestingly, this variance does not depend on the graph structure. For the proof we introduce a duality between our processes and a process of two correlated random walks. We also analyse the convergence time for both models and for arbitrary graphs, showing bounds on the time T-epsilon required to make all node values 'epsilon-close' to each other. Our bounds are asymptotically tight under some assumptions on the distribution of the initial values.

关键词： distributed averaging Dual Processes Stochastic Processes Random Walks

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distributed averaging over communication networks: Fragility, robustness and opportunities

Distributed averaging over communication networks: Fragility...

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作者： Wang, Jing Iowa State University

学位级别：Ph.D.

distributed averaging, a canonical operation among many natural interconnected systems, has found applications in a tremendous variety of applied fields, including statistical physics, signal processing, systems and control, communication and social science. As information exchange is a central part of distributed averaging systems, it is of practical as well as theoretical importance to understand various properties/limitations of those systems in the presence of communication constraints and devise new algorithms to alleviate those limitations. We study the fragility of a popular distributed averaging algorithm when the information exchange among the nodes is limited by communication delays, fading connections and additive noise. We show that the otherwise well studied and benign multi-agent system can generate a collective global complex behavior. We characterize this behavior, common to many natural and human-made interconnected systems, as a collective hyper-jump diffusion process and as a Lévy flights process in a special case. We further describe the mechanism for its emergence and predict its occurrence, under standard assumptions, by checking the Mean Square instability of a certain part of the system. We show that the strong connectivity property of the network topology guarantees that the complex behavior is global and manifested by all the agents in the network, even though the source of uncertainty is localized. We provide novel computational analysis of the MS stability index under spatially invariant structures and gain certain qualitative as well as quantitative insights of the system. We then focus on design of agents' dynamics to increase the robustness of distributed averaging system to topology variations. We provide a general structure of distributed averaging systems where individual agents are modeled by LTI systems. We show the problem of designing agents' dynamics for distributed averaging is equivalent to an [special characters omitted] min

关键词： Consensus Delays distributed averaging distributed Optimization Fading Channels Levy Flight

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