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distributed-Observer-Based Nash Equilibrium Seeking Algorithm for Quadratic Games With Nonlinear Dynamics

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2021年第11期51卷 7260-7268页

作者： Huang, Bomin Zou, Yao Meng, Ziyang Tsinghua Univ Dept Precis Instrument Beijing 100084 Peoples R China

In this article, a class of distributed quadratic games is considered over an undirected graph. The issue on the communication topology restriction is introduced and the players' dynamics are with nonlinear dynamics and unknown time-varying perturbation. A distributed Nash equilibrium seeking algorithm is proposed based on a high-gain observer method, and the convergence is analyzed by the Lyapunov stability theory. It is shown that each player estimates the rival players' states, and the errors between the players' states and the Nash equilibrium are ultimately bounded by a small bound. Moreover, the presented algorithm is free of chattering phenomena because it is designed using the hyperbolic tangent function instead of the signum function to dominant the perturbation. The effectiveness of the proposed algorithm is validated via a simulation of the oligopoly game in which five firms produce the same products in a duopoly market structure.

关键词： Games Nash equilibrium Nonlinear dynamical systems Heuristic algorithms Perturbation methods Cost function Topology distributed algorithms equilibrium seeking Nash equilibrium quadratic games

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Minimal-time complex consensus for multi-agent systems with time delay

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IET CONTROL THEORY AND APPLICATIONS 2022年第12期16卷 1182-1193页

作者： Zou, Chao Yu, Li Yang, Simon Ou, Linlin Zhejiang Univ Technol Coll Informat & Engn Hangzhou 310023 Peoples R China Univ Guelph Sch Engn Guelph ON Canada

This paper studies the minimum time consensus problem for discrete-time multi-agent systems with complex Laplacian delay networks such that each agent can find its complex consensus value in a minimum number of steps using its local observations. The stability analysis is first provided and the convergence condition is derived for complex weighted networks with time delays. Specifically, the delayed multi-agent system is modeled by employing the augmented graph representation. Via adding virtual agents in the augmented systems, the complex consensus is obtained in the networks with bounded time delay if the communication topology digraph of the system has a spanning tree. A decentralized algorithm is proposed for the minimal-time computation of complex consensus based on the information from the robot itself without relying on the external environment. The algorithm hinges on the minimal polynomial of the matrix concerning the augmented graph. Furthermore, the rearrangement of the virtual agents in the augmented system provides an upper bound for the number of agents required to compute the consensus value. Simulation examples demonstrate the effectiveness of our results. The advantage of this approach is that it can be easily deployed on a group of agents to rapidly achieve a complex consensus setting within any delayed networks.

关键词： minimal polynomial distributed algorithms augmented system mobile robots bounded time delay minimum time consensus problem delayed multiagent system augmented graph representation multi-robot systems computational complexity communication topology digraph minimal-time computation decentralized algorithm convergence minimal-time complex consensus stability analysis time delays complex weighted networks discrete time systems convergence condition polynomials complex consensus setting discrete-time multiagent systems virtual agents directed graphs multi-agent systems trees (mathematics) delays complex Laplacian delay networks complex consensus value spanning tree

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distributed Coordinated Reactive Power Control for Voltage Regulation in Distribution Networks

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IEEE TRANSACTIONS ON SMART GRID 2021年第1期12卷 312-323页

作者： Tang, Zhiyuan Hill, David J. Liu, Tao Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada Univ New South Wales Sch Elect Engn & Telecommun Sydney NSW 2052 Australia Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China

In this article, a novel distributed coordinated control framework is proposed to handle the uncertain voltage violations in active distribution networks. It addresses the problem of coordination of different types of devices in a distributed manner. In our control design, on-load tap changers (OLTCs) are firstly employed to handle the potential voltage violations based on the prediction of renewable outputs and load variations. During real-time operation, once an unmanageable voltage violation is detected, the reactive power of distributed energy resources (DERs) will be coordinated immediately to provide fast corrective control. The control schedules of OLTCs are calculated by solving a multitime-step constrained optimization problem via the alternating direction method of multipliers, whereas the reactive power injections of DERs are determined by a novel online distributed algorithm. The effectiveness of the proposed control framework is verified on the modified IEEE 34-bus and 123-bus test feeders.

关键词： Voltage control Reactive power Distribution networks distributed algorithms Approximation algorithms On load tap changers Electric potential Voltage control distributed control reactive power control distribution network on-load tap changer

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Deep Reinforcement Learning for Task Offloading in Mobile Edge Computing Systems

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2022年第6期21卷 1985-1997页

作者： Tang, Ming Wong, Vincent W. S. Univ British Columbia Dept Elect & Comp Engn Vancouver BC V6T 1Z4 Canada

In mobile edge computing systems, an edge node may have a high load when a large number of mobile devices offload their tasks to it. Those offloaded tasks may experience large processing delay or even be dropped when their deadlines expire. Due to the uncertain load dynamics at the edge nodes, it is challenging for each device to determine its offloading decision (i.e., whether to offload or not, and which edge node it should offload its task to) in a decentralized manner. In this work, we consider non-divisible and delay-sensitive tasks as well as edge load dynamics, and formulate a task offloading problem to minimize the expected long-term cost. We propose a model-free deep reinforcement learning-based distributed algorithm, where each device can determine its offloading decision without knowing the task models and offloading decision of other devices. To improve the estimation of the long-term cost in the algorithm, we incorporate the long short-term memory (LSTM), dueling deep Q-network (DQN), and double-DQN techniques. Simulation results show that our proposed algorithm can better exploit the processing capacities of the edge nodes and significantly reduce the ratio of dropped tasks and average delay when compared with several existing algorithms.

关键词： Task analysis Mobile handsets Delays Heuristic algorithms Mobile computing Edge computing distributed algorithms Mobile edge computing computation offloading resource allocation deep reinforcement learning deep Q-learning

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Optimal Eventual Byzantine Agreement Protocols with Omission Failures 23

Optimal Eventual Byzantine Agreement Protocols with Omission...

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

作者： Alpturer, Kaya Halpern, Joseph Y. van der Meyden, Ron Cornell Univ Ithaca NY 14850 USA UNSW Sydney Sydney NSW Australia

ISBN: (纸本)9798400701214

Work on optimal protocols for Eventual Byzantine Agreement (EBA)-protocols that, in a precise sense, decide as soon as possible in every run and guarantee that all nonfaulty agents decide on the same value-has focused on full-information protocols (FIPs), where agents repeatedly send messages that completely describe their past observations to every other agent. While it can be shown that, without loss of generality, we can take an optimal protocol to be an FIP, full information exchange is impractical to implement for many applications due to the required message size. We separate protocols into two parts, the information-exchange protocol and the action protocol, so as to be able to examine the effects of more limited information exchange. We then define a notion of optimality with respect to an information-exchange protocol. Roughly speaking, an action protocol P is optimal with respect to an information-exchange protocol epsilon if, with P, agents decide as soon as possible among action protocols that exchange information according to epsilon. We present a knowledge-based EBA program for omission failures all of whose implementations are guaranteed to be correct and are optimal if the information exchange satisfies a certain safety condition. We then construct concrete programs that implement this knowledge-based program in two settings of interest that are shown to satisfy the safety condition. Finally, we show that a small modification of our program results in an FIP that is both optimal and efficiently implementable, settling an open problem posed by Halpern, Moses, and Waarts (SIAM J. Comput., 2001).

关键词： distributed algorithms Epistemic logic Reasoning about knowledge Byzantine Agreement Consensus Fault tolerance

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Mobile data offloading based on minority game theoretic framework

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WIRELESS NETWORKS 2022年第7期28卷 2967-2982页

作者： Majumder, Bhaswar Venkatesh, T. G. Indian Inst Technol Madras Elect Engn Chennai 600036 Tamil Nadu India

Mobile data offloading is a current-day networking paradigm to channelize certain fraction of the cellular data traffic over unlicensed spectrum of WiFi. In this paper, we present a novel data offloading scheme built upon the exponential learning-based minority game (MG) theory. Performance comparison between cellular and WiFi services with respect to the offered load, has been used to derive an appropriate offloading condition for our proposed MG-based distributed data offloading algorithm. Effectiveness of the MG algorithm is tested by studying its performance through extensive simulation by varying several important parameters, like, pricing parameter beta, cellular offered throughput (S-c), and temperature coefficient of the algorithm (gamma). An effective model for tuning pricing parameter beta with respect to the offered load (named as, Target Pricing scheme) is also presented using reverse engineering approach by considering the dynamic traffic condition. We have provisioned the application of our algorithm in multi-access point environment. We have studied the behaviour of different classes of nodes in heterogeneous population, while applying a MG-based networking algorithm. Through extensive NS3 based simulation we have evaluated the performance of our proposed algorithm in an IEEE 802.11ax environment and studied the effect of MIMO, QoS, transport layer and unsaturated traffic condition.

关键词： Wireless networks Mobile data offloading distributed algorithms Game theory Minority game Pricing model

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Verifying safety of synchronous fault-tolerant algorithms by bounded model checking

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INTERNATIONAL JOURNAL ON SOFTWARE TOOLS FOR TECHNOLOGY TRANSFER 2022年第1期24卷 33-48页

作者： Stoilkovska, Ilina Konnov, Igor Widder, Josef Zuleger, Florian Informal Syst Vienna Austria TU Wien Vienna Austria

Threshold automata are a formalism introduced for modeling, verification, and synthesis of fault-tolerant distributed algorithms for asynchronous systems, that is, in interleaving semantics. Owing to well-known limitations of what can be achieved in purely asynchronous systems, many fault-tolerant distributed algorithms are designed for synchronous or round-based semantics. In this paper, we introduce the synchronous variant of threshold automata and study their applicability and limitations for the verification of synchronous fault-tolerant distributed algorithms. We show that the parameterized reachability problem for synchronous threshold automata is undecidable. Still, we show that many synchronous fault-tolerant distributed algorithms have a bounded diameter, even though the algorithms are parameterized by the number of processes. Hence, bounded model checking can be used for verifying these algorithms. The existence of bounded diameters is the main conceptual insight in this paper. We compute the diameter of several algorithms and check their safety properties, using SMT queries that contain quantifiers for dealing with the parameters symbolically. Surprisingly, performance of the SMT solvers on these queries is very good, reflecting the recent progress in dealing with quantified queries. We found that the diameter bounds of synchronous algorithms in the literature are tiny (from 1 to 8), which makes our approach applicable in practice. For a specific class of algorithms, we also establish a theoretical result on the existence of a diameter, providing a first explanation for our experimental results.

关键词： Parameterized model checking distributed algorithms Fault tolerance Threshold automata

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Parallelized Active Information Gathering Using Multisensor Network for Environment Monitoring

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IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY 2022年第2期30卷 625-638页

作者： Du, Bin Qian, Kun Claudel, Christian Sun, Dengfeng Purdue Univ Sch Aeronaut & Astronaut W Lafayette IN 47907 USA Univ Texas Austin Dept Civil Architectural & Environm Engn Austin TX 78712 USA

Motivated by the application of environment monitoring, this article studies a novel algorithmic framework for solving, in a parallelized manner, the problem of multisensor active information gathering. Unlike the existing methods relying on the fully connected sensor network and sequential processing, our approach builds on the generic network topology and enables individual sensors to simultaneously make their decisions by communicating with the immediate neighbors. Leveraging the cooperation among the multisensor network, we show that the computational complexity of the proposed parallelized algorithm can be greatly reduced compared to the sequential updating schemes, and meanwhile, the suboptimality of obtained solutions is guaranteed. The interconnection between the algorithm complexity and solution quality is explicitly established with respect to the network topology. Based on such interconnection, we further provide the approach to design the optimal sensor network by the given time budget of the algorithm execution. Finally, numerical simulations on a methane emission monitoring scenario are presented to validate the effectiveness of our approach.

关键词： Monitoring Network topology Methane Sensors Computational complexity Optimal control Heuristic algorithms distributed algorithms environment monitoring motion planning multi-sensor network

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Parallel Breadth-First Search and Exact Shortest Paths and Stronger Notions for Approximate Distances 2023

Parallel Breadth-First Search and Exact Shortest Paths and S...

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55th Annual ACM Symposium on Theory of Computing (STOC) part of the ACM Federated Computing Research Conference (FCRC)

作者： Rozhon, Vaclav Haeupler, Bernhard Martinsson, Anders Grunau, Christoph Zuzic, Goran Swiss Fed Inst Technol Zurich Switzerland CMU Pittsburgh PA 15213 USA

ISBN: (纸本)9781450399135

This paper introduces stronger notions for approximate single-source shortest-path distances and gives simple reductions to compute them from weaker standard notions of approximate distances. Strongly-approximate distances isolate, capture, and address the well-known barriers for using approximate distances algorithmically and their reductions directly address these barriers in a clean and modular manner. The reductions are model-independent and require only log(O(1)) black-box approximate distance computations. They apply equally to parallel, distributed, and semi-streaming settings. Strongly (1 +epsilon)-approximate distances are equivalent to exact distances in a (1 + epsilon)-perturbed graph and approximately satisfy the subtractive triangle inequality. In directed graphs, this is sufficient to reduce even exact distance computation to arbitrary (1 + epsilon)-approximate ones. Overall, this paper simplifies, unifies, and cleans up problemspecific ad-hoc solutions developed in many prior works, e.g., for ball-growing routines in undirected graphs and for computing exact distances in directed graphs. Several algorithmic results for parallel and distributed algorithms - some known, some new - are directly implied by our reductions. Applications of particular interest include the first work-efficient sublinear-depth parallel algorithm for breadth-first search and computing exact single-source shortest paths - both major open problems in parallel computing. Given a source vertex in a directed graph with polynomiallybounded nonnegative integer lengths the algorithm computes an exact shortest path tree in.. log(O(1)) work and n(1/2+o(1)) depth. Previously, no parallel algorithm improving the trivial linear depths of Dijkstra's algorithm without significantly increasing the work was known, even for the case of undirected and unit-length graphs, i.e., for computing a breadth-first-search tree. This result was independently obtained by Fineman and Cao.

关键词： parallel algorithms distributed algorithms bfs shortest path exact distances approximate distances

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Federated Learning Meets Multi-Objective Optimization

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2022年第4期9卷 2039-2051页

作者： Hu, Zeou Shaloudegi, Kiarash Zhang, Guojun Yu, Yaoliang Univ Waterloo Cheriton Sch Comp Sci Waterloo ON N2L 3G1 Canada Amazon Canada Amazon Advertising Toronto ON M5H 4A9 Canada Huawei Noah Arks Lab Montreal PQ H3N 1X9 Canada

Federated learning has emerged as a promising, massively distributed way to train a joint deep model over large amounts of edgedevices while keeping private user data strictly on device. In this work, motivated from ensuring fairness among users and robustness against malicious adversaries, we formulate federated learning as multi-objective optimization and propose a new algorithm FedMGDA+ that is guaranteed to converge to Pareto stationary solutions. FedMGDA+ is simple to implement, has fewer hyperparameters to tune, and refrains from sacrificing the performance of any participating user. We establish the convergence properties of FedMGDA+ and point out its connections to existing approaches. Extensive experiments on a variety of datasets confirm that FedMGDA+ compares favorably against state-of-the-art.

关键词： Optimization Collaborative work Servers Robustness Convergence Machine learning algorithms Arithmetic Pareto optimization distributed algorithms Federated learning Edge computing Machine learning Neural networks

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