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distributed Average Tracking in Weight-Unbalanced Directed Networks

IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2021年第9期66卷 4436-4443页

作者： Sun, Shan Chen, Fei Ren, Wei Univ Calif Riverside Dept Elect & Comp Engn Riverside CA 92521 USA Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110004 Peoples R China Northeastern Univ Qinhuangdao Sch Control Engn Qinhuangdao 066004 Hebei Peoples R China

This article studies a distributed average tracking (DAT) problem, in which a collection of agents work collaboratively, subject to local communication, to track the average of a set of reference signals, each of which is available to a single agent. Our primary objective is to seek a design methodology for DAT under possibly weight-unbalanced directed networks-the most general and thus most challenging case from the network topology perspective, which has few results in the literature. For this purpose, we propose a distributed algorithm based on a chain of two integrators that are coupled with a distributed estimator. It is found that the convergence depends on not only the network topology but also the deviations among the reference signal accelerations. Another primary interest of this article stems from the dynamics perspective-a point perceived as a main source of control design difficulty for multiagent systems. Indeed, we devise a nonlinear algorithm that is capable of achieving DAT under weight-unbalanced directed networks for agents subject to high-order integrator dynamics. The results show that the convergence to the vicinity of the average of the reference signals is guaranteed as long as the signals' states and control inputs are all bounded. Both algorithms are robust to initialization errors, i.e., DAT is insured even if the agents are not correctly initialized, enabling the potential applications in a wider spectrum of application domains.

关键词： Heuristic algorithms Directed graphs Laplace equations Eigenvalues and eigenfunctions distributed algorithms Convergence Network topology distributed average tracking multiagent system weight-unbalanced directed graphs

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Single-source shortest paths in the CONGEST model with improved bounds

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distributed COMPUTING 2022年第4期35卷 357-374页

作者： Chechik, Shiri Mukhtar, Doron Tel Aviv Univ Tel Aviv Israel

Computing shortest paths from a single source is one of the central problems studied in the CONGEST model of distributed computing. After many years in which no algorithmic progress was made, Elkin [STOC '17] provided the first improvement over the distributed Bellman-Ford algorithm. Since then, several improved algorithms have been published. The state-of-the-art algorithm for weighted directed graphs (with polynomially bounded non-negative integer weights) requires (O) over tilde (min{root nD(1/2), root nD(1/4) + n(3/5) + D}) rounds [Forster and Nanongkai, FOCS '18], which is still quite far from the known lower bound of (Omega) over tilde(root n + D) rounds [Elkin, STOC '04];here D is the diameter of the underlying network and n is the number of vertices in it. For the (1+ o(1))-approximate version of this problem and the same class of graphs, Forster and Nanongkai [FOCS 18] obtained a better upper bound of (O) over tilde (root nD(1/4) + D) rounds. In the same paper, they stated that achieving the same bound for the exact case remains a major open problem. In this paper we resolve the above mentioned problem by devising a new randomized algorithm for computing shortest paths from a single source in (O) over tilde (root nD(1/4) + D) rounds. Our algorithm is based on a novel weight-modifying technique that allows us to compute approximate distances that preserve a certain form of the triangle inequality for the edges in the graph.

关键词： Single-source shortest paths distributed algorithms Overlay networks

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Proportionally fair flow markets for transportation networks

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2022年 157卷 24-41页

作者： Aalami, Soheila Kattan, Lina Univ Calgary Dept Civil Engn Calgary AB Canada

The concept of proportionally fair markets for transportation networks is studied. The goal is to find methods for flow allocation to origin/destination pairs in urban communities which is fair, efficient, and able to dynamically adapt to the changes in origin/destinations and traffic network. Two flow markets are designed and studied. distributed and dynamic algorithms are developed to find the proportional fair allocation of flow among competing origin/destinations. Additionally, existence, uniqueness and stability of the equilibrium points are proved for both markets. Our numerical simulations supplement the stability and practicality of our proposed algorithms.

关键词： Flow markets Proportional fairness Transportation networks Flow assignment distributed algorithms

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Dispersion of mobile robots using global communication

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JOURNAL OF PARALLEL AND distributed COMPUTING 2022年 161卷 100-117页

作者： Kshemkalyani, Ajay D. Molla, Anisur Rahaman Sharma, Gokarna Univ Illinois Chicago IL USA Indian Stat Inst Kolkata India Kent State Univ Kent OH 44242 USA

The dispersion problem on graphs asks k <= n robots placed initially arbitrarily on the nodes of an n-node anonymous graph to reposition autonomously to reach a configuration in which each robot is on a distinct node of the graph. This problem is of significant interest due to its relationship to other fundamental robot coordination problems, such as exploration, scattering, load balancing, and relocation of self-driven electric cars (robots) to recharge stations (nodes). In this paper, we consider dispersion using the global communication model where a robot can communicate with any other robot in the graph (but the graph is unknown to robots). We provide two novel deterministic algorithms for arbitrary graphs in a synchronous setting where all robots perform their actions in every time step. Our first algorithm is based on a DFS traversal and guarantees (i) O(k Delta) steps runtime using O (log(k + Delta))) bits at each robot and (ii) O(min(m, k Delta)) steps runtime using O(Delta + log k) bits at each robot, where m is the number of edges and Delta is the maximum degree of the graph. The second algorithm is based on a BFS traversal and guarantees O ((D + k)Delta(D + Delta)) steps runtime using O (log D + Delta log k)) bits at each robot, where D is the diameter of the graph. Our results complement the existing results established using the local communication model where a robot can communication only with other robots present at the same node. (C) 2021 Elsevier Inc. All rights reserved.

关键词： Multi-agent systems Autonomous mobile robots Dispersion distributed algorithms Time and memory complexity

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Interactive Inference Under Information Constraints

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IEEE TRANSACTIONS ON INFORMATION THEORY 2022年第1期68卷 502-516页

作者： Acharya, Jayadev Canonne, Clement L. Liu, Yuhan Sun, Ziteng Tyagi, Himanshu Cornell Univ Sch Elect & Comp Engn Ithaca NY 14850 USA Univ Sydney Sch Comp Sci Sydney NSW 2006 Australia Indian Inst Sci Dept Elect Commun Engn Bengaluru 560012 India

We study the role of interactivity in distributed statistical inference under information constraints, e.g., communication constraints and local differential privacy. We focus on the tasks of goodness-of-fit testing and estimation of discrete distributions. From prior work, these tasks are well understood under noninteractive protocols. Extending these approaches directly for interactive protocols is difficult due to correlations that can build due to interactivity;in fact, gaps can be found in prior claims of tight bounds of distribution estimation using interactive protocols. We propose a new approach to handle this correlation and establish a unified method to establish lower bounds for both tasks. As an application, we obtain optimal bounds for both estimation and testing under local differential privacy and communication constraints. We also provide an example of a natural testing problem where interactivity helps.

关键词： Protocols Testing Task analysis Estimation Privacy Correlation Complexity theory distributed algorithms inference algorithms estimation statistics minimax techniques data privacy communication channels

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Network Flows That Solve Sylvester Matrix Equations

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2022年第12期67卷 6731-6738页

作者： Deng, Wen Hong, Yiguang Anderson, Brian D. O. Shi, Guodong Tongji Univ Dept Control Sci & Engn Shanghai 201804 Peoples R China Tongji Univ Shanghai Res Inst Intelligent Autonomous Syst Shanghai 201210 Peoples R China Hangzhou Dianzi Univ Hangzhou 310018 Peoples R China Data61 CSIRO Canberra ACT 2601 Australia Australian Natl Univ Res Sch Elect Energy & Mat Engn Canberra ACT 2600 Australia Univ Sydney Australian Ctr Field Robot Sch Aerosp Mech & Mechatron Engn Sydney NSW 2006 Australia

In this article, we study methods to solve a Sylvester equation in the form of AX + XB = C for given matrices A, B, C is an element of R-nxn, inspired by the distributed linear equation flows. The entries of A. B. and C are separately partitioned into a number of pieces (or sometimes we permit these pieces to overlap), which are allocated to nodes in a network. Nodes hold a dynamic state shared among their neighbors defined from the network structure. Natural partial or full row , column partitions and block partitions of the data A, B, and C are formulated by use of the vectorized matrix equation. We show that existing network flows for distributed linear algebraic equations can be extended to solve this special form of matrix equations over networks. A "consensus + projection + symmetrization" flow is also developed for equations with symmetry constraints on the matrix variables. We prove the convergence of these flows and obtain the fastest convergence rates that these flows can achieve regardless of the choices of node interaction strengths and network structures.

关键词： Convergence rate distributed algorithms network flows Sylvester equation

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distributed Nash Equilibrium Seeking With Limited Cost Function Knowledge via a Consensus-Based Gradient-Free Method

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2021年第4期66卷 1832-1839页

作者： Pang, Yipeng Hu, Guoqiang Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

This article considers a distributed Nash equilibrium seeking problem, where the players only have partial access to other players' actions, such as their neighbors' actions. Thus, the players are supposed to communicate with each other to estimate other players' actions. To solve the problem, a leader-following consensus gradient-free distributed Nash equilibrium seeking algorithm is proposed. This algorithm utilizes only the measurements of the player' local cost function without the knowledge of its explicit expression or the requirement on its smoothness. Hence, the algorithm is gradient-free during the entire updating process. Moreover, the analysis on the convergence of the Nash equilibrium is studied for the algorithm with both diminishing and constant step-sizes, respectively. Specifically, in the case of diminishing step-size, it is shown that the players' actions converge to the Nash equilibrium almost surely, while in the case of fixed step-size, the convergence to the neighborhood of the Nash equilibrium is achieved. The performance of the proposed algorithm is verified through numerical simulations.

关键词： Games Nash equilibrium Cost function Convergence Protocols Heuristic algorithms Approximation algorithms distributed algorithms game theory gradient-free methods Nash equilibrium (NE) seeking noncooperative games

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Multihop routing with static and distributed clustering in WSNs

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WIRELESS NETWORKS 2021年第6期27卷 3797-3809页

作者： Abasikeles-Turgut, Ipek Iskenderun Tech Univ Comp Engn Dept Antakya Turkey

Nowadays, Wireless Sensor Networks are one of the fundamental infrastructures for IoT technology. Although WSN has been researched for a decade, providing energy efficiency for resource-constrained sensor nodes is still a hot topic given the widespread usage of real-time WSN applications. For ensuring scalability, recent studies focus on multi-hop routing schemes. In this paper, a fully distributed, multi-hop intra and inter-cluster communication based static clustering scheme (MI(2)RSDiC) is proposed for WSNs. Differently from the studies in literature, MI(2)RSDiC suggests a limited re-evaluation opportunity to the nodes in clustering phase for optimized decision, an adaptive threshold-based cluster head alteration for energy efficiency and a multi-hop communication at every transmission stage for supporting large-scale WSNs. The proposed approach is compared with recent approaches and the results show that MI(2)RSDiC yields the highest lifetime of the network with achieving the least energy consumption and the largest amount of collected data among the equivalent approaches.

关键词： Clustering methods distributed algorithms Energy efficiency Routing protocols Wireless sensor networks

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distributed Generalized Nash Equilibrium Seeking in Aggregative Games on Time-Varying Networks

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2021年第5期66卷 2061-2075页

作者： Belgioioso, Giuseppe Nedic, Angelia Grammatico, Sergio Eindhoven Univ Technol Control Syst Grp NL-5612 AZ Eindhoven Netherlands Arizona State Univ Sch Elect Comp & Energy Engn Tempe AZ 85287 USA Delft Univ Technol Delft Ctr Syst & Control DCSC NL-2628 CD Delft Netherlands

We design the first fully distributed algorithm for generalized Nash equilibrium seeking in aggregative games on a time-varying communication network, under partial-decision information, i.e., the agents have no direct access to the aggregate decision. The algorithm is derived by integrating dynamic tracking into a projected pseudo-gradient algorithm. The convergence analysis relies on the framework of monotone operator splitting and the Krasnosel'skii-Mann fixed-point iteration with errors.

关键词： Games Heuristic algorithms Nash equilibrium Communication networks Convergence Couplings Aggregates distributed algorithms multiagent systems optimization method network theory

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A distributed Double-Newton Descent Algorithm for Cooperative Energy Management of Multiple Energy Bodies in Energy Internet

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2021年第9期17卷 5993-6003页

作者： Li, Yushuai Gao, David Wenzhong Gao, Wei Zhang, Huaguang Zhou, Jianguo Northeastern Univ Sch Informat Sci & Engn Shenyang 110004 Peoples R China Univ Denver Dept Elect & Comp Engn Denver CO 80208 USA Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110004 Peoples R China Northeastern Univ Sch Informat Sci & Engn Shenyang 110004 Peoples R China Tsinghua Univ Tsinghua Shenzhen Int Grad Sch Tsinghua SIGS Tsinghua Berkeley Shenzhen Inst TBSI Shenzhen 518055 Peoples R China

This article investigates the problem of distributed cooperative energy management of multiple energy bodies with the consideration of both the optimal energy generation/consumption of each participant within single energy body and the optimal energy distribution on the interconnected lines between any pair of energy bodies. First, we define the physical and communication structure of the system formed by many energy bodies, each of which is viewed as a multienergy prosumer. Then, a distributed energy management model is proposed to achieve not only maximum profits of overall energy generation and consumption, but also minimum cost of energy delivery. To address this issue, a distributed double-Newton descent (DDND) algorithm is proposed, which possesses two advantages. On the one hand, by employing second-order information, the concept of Newton descent is embedded into the implementation of the proposed algorithm, resulting in faster convergence speed. On the other hand, the proposed algorithm performs in a fully distributed fashion. As a consequence, each participant can locally obtain its optimal operation as well as the global energy market clearing prices;meanwhile, each energy router can locally obtain the optimal exchanged energy with its neighbor energy routers. Moreover, we prove that the proposed DDND algorithm can asymptotically converge to the global optimal point. As a result, the correctness of the DDND algorithm can be guaranteed in theory. Finally, simulation results validate the effectiveness of the proposed algorithm.

关键词： Energy management Microgrids Smart grids Informatics distributed algorithms Economics Pipelines distributed algorithm energy body (EB) energy internet (EI) Newton descent

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