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Event-Triggered Approximate Byzantine Consensus With Multi-Hop Communication

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2023年 71卷 1742-1754页

作者： Yuan, Liwei Ishii, Hideaki Hunan Univ Coll Elect & Informat Engn Changsha 410082 Peoples R China Tokyo Inst Technol Dept Comp Sci Yokohama 2268502 Japan

In this article, we consider a resilient consensus problem for the multi-agent network where some of the agents are subject to Byzantine attacks and may transmit erroneous state values to their neighbors. In particular, we develop two event-triggered update schemes to tackle this problem as well as reduce the communication for each agent. Our approach is based on the mean subsequence reduced (MSR) algorithm with agents being capable to communicate with multi-hop neighbors through relaying process. Since communication delays are critical in such an environment, we provide necessary graph conditions for the proposed algorithms to perform well with delays in the communication. Moreover, a novel multi-hop relay scheme with event-triggered feature is proposed. It can reduce more transmissions than the conventional one-hop event-triggered algorithm. We also highlight that through multi-hop communication, the network connectivity can be reduced especially in comparison with the common one-hop communication case. Lastly, we show the effectiveness of the proposed algorithms by numerical examples.

关键词： Signal processing algorithms Relays Spread spectrum communication Delays Robustness Resilience Protocols Resilient consensus distributed algorithms byzantine attack event-triggered updates multi-hop communication

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Dynamic Optimization of Random Access in Deadline-Constrained Broadcasting

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2023年第4期10卷 2059-2073页

作者： Gong, Aoyu Zhang, Yijin Deng, Lei Liu, Fang Li, Jun Shu, Feng Nanjing Univ Sci & Technol Sch Elect & Opt Engn Nanjing 210094 Peoples R China Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China Shenzhen Univ Coll Elect & Informat Engn Shenzhen 518060 Peoples R China Chinese Univ Hong Kong Dept Informat Engn Shatin Hong Kong Peoples R China Hainan Univ Sch Informat & Commun Engn Haikou Peoples R China

This paper considers dynamic optimization of random access in deadline-constrained broadcasting with frame-synchronized traffic. Under the non-retransmission setting, we define a dynamic control scheme that allows each active node to determine the transmission probability based on the local knowledge of current delivery urgency and contention intensity (i.e., the number of active nodes). For an idealized environment where the contention intensity is completely known, we develop a Markov Decision Process (MDP) framework, by which an optimal scheme for maximizing the timely delivery ratio (TDR) can be explicitly obtained. For a realistic environment where the contention intensity is incompletely known, we develop a Partially Observable MDP (POMDP) framework, by which an optimal scheme can only in theory be found. To overcome the infeasibility in obtaining an optimal or near-optimal scheme from the POMDP framework, we investigate the behaviors of the optimal scheme for extreme cases in the MDP framework, and leverage intuition gained from these behaviors together with an approximation on the contention intensity knowledge to propose a heuristic scheme for the realistic environment with TDR close to the maximum TDR in the idealized environment. We further generalize the heuristic scheme to support retransmissions. Numerical results are provided to validate our study.

关键词： distributed algorithms dynamic optimization random access delivery deadline

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Clock synchronization based on pulse with propagation delay eliminated in wireless sensor networks

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IET COMMUNICATIONS 2023年第17期17卷 1955-1961页

作者： Liu, Wei Fan, Ruijie Mai, Yiyuan Wan, Zehan Natl Univ Def Technol Coll Elect Sci Changsha Peoples R China

Clock synchronization is indispensable for numerous applications of wireless sensor networks (WSNs). When no common reference clock is available, the nodes must employ distributed synchronization techniques. This paper proposes, a distributed pulse-based clock synchronisation approach, wherein the propagation delay is eliminated through signal ping-pongs between neighbouring nodes. Such an approach can jointly estimate the clock skew and offset without requiring any reference clock. The whole synchronization process is completed at the physical (PHY) layer, effectively avoiding the random delay caused by packet queuing and retransmission. Simulation results show that the proposed approach can achieve higher synchronization accuracy compared with other existing methods.

关键词： distributed algorithms frequency estimation parameter estimation phase estimation wireless sensor networks

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An Incremental Gradient Method for Optimization Problems With Variational Inequality Constraints

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2023年第12期68卷 7879-7886页

作者： Kaushik, Harshal D. Samadi, Sepideh Yousefian, Farzad Bayer US LLC St. Louis MO 63141 USA Rutgers State Univ Dept Ind & Syst Engn New Brunswick NJ 08854 USA

We consider minimizing a sum of agent-specific nondifferentiable merely convex functions over the solution set of a variational inequality (VI) problem in that each agent is associated with a local monotone mapping. This problem finds an application in computation of the best equilibrium in nonlinear complementarity problems arising in transportation networks. We develop an iteratively regularized incremental gradient method where at each iteration, agents communicate over a directed cycle graph to update their solution iterates using their local information about the objective and the mapping. The proposed method is single-timescale in the sense that it does not involve any excessive hard-to-project computation per iteration. We derive nonasymptotic agent-wise convergence rates for the suboptimality of the global objective function and infeasibility of the VI constraints measured by a suitably defined dual gap function. The proposed method appears to be the first fully iterative scheme equipped with iteration complexity that can address distributed optimization problems with VI constraints over cycle graphs.

关键词： Computational complexity distributed algorithms mathematical programming optimization methods

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A Hierarchical Adaptive Leader Election Algorithm for Crash-Recovery distributed Systems 24

A Hierarchical Adaptive Leader Election Algorithm for Crash-...

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13th Latin-American Symposium on Dependable and Secure Computing

作者： Rodrigues, Luiz Antonio Silva Freitas, Allan Edgard Duarte, Elias Procopio, Jr. Fulber-Garcia, Vinicius Western Parana State Univ Cascavel Parana Brazil Fed Inst Bahia Salvador BA Brazil Univ Fed Parana Dept Informat Curitiba Parana Brazil

ISBN: (纸本)9798400717406

Leader election is one of the basic building blocks of distributed systems. Multiple different distributed applications employ a leader for decision making or as a coordinator. Traditional leader election algorithms are usually based on all-to-all communications and scales poorly. This work presents a hierarchical adaptive leader election algorithm for distributed systems under the crash-recovery fault model, which allows processes to maintain secondary non-volatile memory. The proposed solution is based on the vCube virtual topology, which presents multiple logarithmic properties, being scalable by definition. One of the contributions of the work is that it is the first to adapt the vCube to the crash-recovery model. The leader is the correct process with the smallest identifier, among those that are most stable, i.e. have failed and recovered the least number of times. The algorithm is adaptive in the sense that processes that change from stable to unstable receive a penalty in order to avoid slowing down the election. Simulation results comparing with the traditional approach show that the proposed solution significantly reduces the number of messages required for leader election, as well as the time to execute a single testing round.

关键词： Dependability Fault-Tolerance Unreliable Failure Detectors Autonomic Systems distributed algorithms

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Dynamical Primal-Dual Nesterov Accelerated Method and Its Application to Network Optimization

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2023年第3期68卷 1760-1767页

作者： Zeng, Xianlin Lei, Jinlong Chen, Jie Beijing Inst Technol Sch Automat Key Lab Intelligent Control & Decis Complex Syst Beijing 100081 Peoples R China Tongji Univ Shanghai Res Inst Intelligent Autonomous Syst Dept Control Sci & Engn Shanghai 200070 Peoples R China

This article develops a continuous-time primal-dual accelerated method with an increasing damping coefficient for a class of convex optimization problems with affine equality constraints. This article analyzes critical values for parameters in the proposed method and prove that the rate of convergence in terms of the duality gap function is O((1)/(t)2 ) by choosing suitable parameters. As far as we know, this is the first continuous-time primal dual accelerated method that can obtain the optimal rate. Then, this article applies the proposed method to two network optimization problems, a distributed optimization problem with consensus constraints and a distributed extended monotropic optimization problem, and obtains two variant distributed algorithms. Finally, numerical simulations are given to demonstrate the efficacy of the proposed method.

关键词： Convergence Convex functions Cost function distributed algorithms Gradient methods Damping Trajectory Continuous-time algorithm Nesterov's accelerated method network optimization primal-dual method

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Federated Consensus-Based Algorithm for Stable Recovery of Sparse Signals

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2023年第12期72卷 15719-15731页

作者： Qian, Rongrong Qi, Yuan Xue, Yue Zhou, Tianzhi Zhang, Jiyan Beijing Univ Posts & Telecommun Sch Artificial Intelligence Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun Beijing Key Lab Work Safety Intelligent Monitoring Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun Sch Elect Engn Beijing 100876 Peoples R China

In this article, we develop a new algorithm, named federated consensus-based algorithm (FCB), for sparse recovery, and show its performance in terms of both support recovery and signal recovery. Specifically, FCB is designed on the basis of the federated computational architecture, to increase the computational parallelism and accelerate the convergence. The algorithm design is realized by integrating accelerated projection-based consensus (APC) with greedy techniques. Then, the conditions of exact support recovery and an upper bound of signal recovery error are derived for FCB in the noisy case. From the explicit expression of the signal recovery error bound, it is confirmed that FCB can stably recover sparse signals under appropriate conditions using the coherence statistic of the measurement matrix and the minimum magnitude of nonzero elements of the signal. Experimental results illustrate the performance of FCB, validating our derived conditions of exact support recovery and upper bound of signal recovery error. In summary, FCB utilizes the federated computational architecture, enabling high parallelism and fast convergence, and uses greedy techniques to guarantee stable recovery performance.

关键词： Stable sparse recovery distributed algorithms federated computational architecture performance analysis

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Detecting the Most Vital Articulation Points in Wireless Multi-Hop Networks

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IEEE-ACM TRANSACTIONS ON NETWORKING 2023年第5期31卷 2389-2402页

作者： Akram, Vahid Khalilpour Ugurlu, Onur Ege Univ Int Comp Inst TR-35100 Izmir Turkiye Izmir Bakircay Univ Fac Engn & Architecture TR-35665 Izmir Turkiye

An articulation point is a node whose removal partitions the network into disconnected segments. The articulation points may affect the reliability and efficiency of wireless multi hop networks from different aspects. Although all articulation points destroy the connectivity of the network, their negative impact on the network is not equal. Removing some articulation points may disconnect a large subset of nodes or generate a large number of partitions, while removing some other articulation points may only disconnect a few nodes. In this paper, we present two novel problems for identifying the most vital articulation points that significantly impact the network. The first problem is finding the p most important articulation points that minimize the largest connected component in the remaining network. The second problem is finding the p most important articulation points whose removal maximizes the number of partitions in the network. We prove that both problems are NP-Hard and propose a distributed algorithm to identify the vital articulation points in both problems. The proposed algorithm establishes a distributed depth-first search tree to identify the articulation points, assigns a score to each articulation point, and selects the prominent articulation points based on their scores. We compare the proposed algorithm with a brute force-based exact algorithm. The simulation result shows that after removing the detected prominent articulation points by the proposed algorithm, the maximum difference between the largest partition size and the number of partitions with the optimal solutions are less than 27.6% and 28.2%, respectively, while the sent bytes of the proposed algorithm can be 89.9% lower.

关键词： distributed algorithms articulation points connected components critical nodes

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Adaptive Synchronization for Networked Parabolic PDE Systems With Uncertain Nonlinear Actuator Dynamics

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2023年第5期70卷 2167-2178页

作者： Zheng, Yukan Li, Yuan-Xin Ahn, Choon Ki Qingdao Univ Sch Automat Shandong Key Lab Ind Control Technol Qingdao 266071 Peoples R China Liaoning Univ Technol Coll Sci Jinzhou 121001 Peoples R China Korea Univ Sch Elect Engn Seoul 136701 South Korea

This article focuses on the synchronization control of networked uncertain parabolic partial differential equations (PDEs) with uncertain nonlinear actuator dynamics. Compared to existing networked PDE systems, control input occurs in ordinary differential equation (ODE) subsystems rather than in PDE ones. Compared to existing results, where the exact system parameters must be known for the entire system, this paper further considers parabolic PDE-ODE systems with unknown parameters affecting the interior of the PDE domain. Due to the unknown parameters and uncertain nonlinear actuator dynamics, the existing distributed algorithms and stability analysis tools cannot be utilized to solve the synchronization problem of cascaded parabolic systems. To address this difficulty, this study designs a novel passive identifier to estimate the states and unknown parameters. Subsequently, based on the passive identifier and Lyapunov function method, a synchronization controller is presented for cascaded parabolic PDE systems to ensure that the synchronization control and the boundedness of all the closed-loop signals are achieved. Lastly, the effectiveness of the obtained results is illustrated using simulation.

关键词： Synchronization Actuators Mathematical models Heating systems Uncertainty Lyapunov methods distributed algorithms parabolic PDE multi-agent systems actuator dynamics nonlinearity uncertainty

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UNDERSTANDING A CLASS OF DECENTRALIZED AND FEDERATED OPTIMIZATION algorithms: A MULTIRATE FEEDBACK CONTROL PERSPECTIVE*

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SIAM JOURNAL ON OPTIMIZATION 2023年第2期33卷 652-683页

作者： Zhang, Xinwei Hong, Mingyi Elia, Nicola Univ Minnesota ECE Dept Minneapolis MN 55455 USA

distributed algorithms have been playing an increasingly important role in many applications such as machine learning, signal processing, and control. Significant research efforts have been devoted to developing and analyzing new algorithms for various applications. In this work, we provide a fresh perspective to understand, analyze, and design distributed optimization algorithms. Through the lens of multirate feedback control, we show that a wide class of distributed algorithms, including popular decentralized/federated schemes, can be viewed as discretizing a certain continuous-time feedback control system, possibly with multiple sampling rates, such as decentralized gradient descent, gradient tracking, and federated averaging. This key observation not only allows us to develop a generic framework to analyze the convergence of the entire algorithm class, but, more importantly, it also leads to an interesting way of designing new distributed algorithms. We develop the theory behind our framework and provide examples to highlight how the framework can be used in practice.

关键词： distributed algorithms convergence analysis control perspective

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