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International Conference on distributed Computing Systems

作者： Yiming Zeng Yaodong Huang Ji Liu Yuanyuan Yang Stony Brook University Stony Brook NY USA

ISBN: (数字)9781728170022

ISBN: (纸本)9781728170039

distributed edge caching has drawn great attention with the fast development of smart edge devices. Caching popular contents in the edge can reduce latency and improve the quality of service of edge mobile users. Meanwhile, the data privacy in the edge is critical to preserve the privacy of individual users and devices. How to jointly determine the caching and routing policy in the edge network in a distributed manner and simultaneously design the proper privacy preserving mechanism are challenging. We tackle these challenges in two progressive steps. First, we design a distributed algorithm which can achieve the global optimum. Second, we propose a privacy-preserving mechanism based on differential privacy and prove the privacy guarantee. We conduct extensive numerical simulations based on real-world requests to evaluate the performance of the proposed distributed algorithm and the privacy mechanism. Results highlight a significant improvement of the proposed distributed algorithm while only up to 10.1% of the total serving cost increased by the privacy mechanism.

关键词： Privacy Differential privacy distributed databases Quality of service Routing Numerical simulation distributed algorithms

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Online distributed Edge Caching for Mobile Data Offloading in 5G Networks

Online Distributed Edge Caching for Mobile Data Offloading i...

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International Workshop on Quality of Service

作者： Yiming Zeng Yaodong Huang Zhenhua Liu Yuanyuan Yang Stony Brook University Stony Brook NY USA

ISBN: (数字)9781728168876

ISBN: (纸本)9781728168883

Edge caching is an effective approach to improve the quality of service for mobile users and therefore a critical component for 5G networks. Despite the importance, it is not clear how to determine which contents to cache and how to the serve requests in 5G networks to minimize the total operational cost in a distributed and online manner, especially when some mobile users can be served by multiple small base stations. In this paper, we formulate an optimization problem to jointly decide the caching policy and the routing decision. There are two challenges: the need for distributed control and the lack of future information. We therefore develop an online distributed algorithm with provable performance guarantees in terms of convergence and competitive ratio compared to the offline optimal solution. Numerical simulations based on real-world traces highlight the significant performance improvement compared to existing baselines.

关键词： Routing 5G mobile communication Quality of service Optimization Base stations distributed algorithms Bandwidth

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ADMM Algorithm based distributed Energy Management in Active Distribution Network

ADMM Algorithm based Distributed Energy Management in Active...

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National Power Systems Conference (NPSC)

作者： Satish Kumar Singh P. B. S. Kiran Naran M. Pindoriya Discipline of Electrical Engineering IIT Gandhinagar Palaj India

ISBN: (数字)9781728185521

ISBN: (纸本)9781728185552

distributed energy management algorithms are remarkably efficient in resolving load variation issues and addressing a high peak to average power ratio. A distributed algorithm promotes individual participation, bilateral coordination, data privacy, and consumers' economic benefit. This paper presents an alternating direction method of multipliers (ADMM) based distributed algorithm for energy management in a distribution network. It decomposes the centralized energy management problem into a distribution system operator (DSO) and load aggregator (LA) level sub-problems. The DSO objective is to minimize energy cost and power loss in the network, whereas LA intends to reduce its energy consumption cost. The DSO and LA optimization problems are solved independently and coordinated via a central coordinator. The algorithm is tested on a modified 15-node distribution network to substantiate its effectiveness. The simulation results are presented for flexible loads, solar PV generation, and battery energy storage systems. Also, we analyzed the impact of the penalty factor on the algorithm convergence and the network power consumption.

关键词： Distribution networks Convex functions Batteries distributed algorithms Optimization Tuning Convergence

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distributed Nash Equilibrium Seeking Design in Network of Uncertain Linear Multi-agent Systems

Distributed Nash Equilibrium Seeking Design in Network of Un...

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International Conference on Control and Automation (ICCA)

作者： Xinyu Liu Yawei Zhang Xinghu Wang Haibo Ji University of Science and Technology of China Hefei China

ISBN: (数字)9781728190938

ISBN: (纸本)9781728190945

In this paper, we consider distributed Nash equilibrium seeking design for aggregative games over networks. The agents (players) are specified by high-order uncertain linear dynamics. By combining gradient method and distributed average consensus technique, we first construct a dynamic compensator that can generate a fictitious reference signal converging to the necessary Nash equilibrium point and convert the distributed Nash equilibrium seeking problem into a tracking problem. Then, we solve the latter tracking problem, giving rise to a two-step distributed Nash equilibrium seeking design robust against parametric uncertainties in agents.

关键词： Games Heuristic algorithms Nash equilibrium Power system dynamics Multi-agent systems Gradient methods distributed algorithms

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Accelerated Voltage Regulation in Multi-Phase Distribution Networks Based on Hierarchical distributed Algorithm

Accelerated Voltage Regulation in Multi-Phase Distribution N...

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IEEE General Meeting Power& Energy Society

作者： Xinyang Zhou Zhiyuan Liu Changhong Zhao Lijun Chen National Renewable Energy Laboratory Energy System Integration Computer Science University of Colorado Boulder The Chinese University of Hongkong

ISBN: (数字)9781728155081

ISBN: (纸本)9781728155098

- We propose a hierarchical distributed algorithm to solve optimal power flow (OPF) problems that aim at dispatching controllable distributed energy resources (DERs) for voltage regulation at minimum cost. The proposed algorithm features unprecedented scalability to large multi-phase distribution networks by jointly exploring the tree/subtrees structure of a large radial distribution network and the structure of the linearized distribution power flow (LinDistFlow) model to derive a hierarchical, distributed implementation of the primal-dual gradient algorithm that solves OPF. The proposed implementation significantly reduces the computation loads compared to the centrally coordinated implementation of the same primal-dual algorithm without compromising optimality. Numerical results on a 4,521-node test feeder show that the designed algorithm achieves more than 10-fold acceleration in the speed of convergence compared to the centrally coordinated primal-dual algorithm through reducing and distributing computational loads.

关键词： Scalability Distribution networks Numerical models Acceleration Voltage control distributed algorithms Load flow

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A new approach to the stability analysis of continuous-time distributed consensus algorithms

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NEURAL NETWORKS 2013年 46卷 242-248页

作者： Liu, Bo Lu, Wenlian Chen, Tianping Fudan Univ Key Lab Nonlinear Math Sci Sch Math Sci Shanghai 200433 Peoples R China Univ Tokyo Inst Ind Sci Meguro Ku Tokyo 1538505 Japan Fudan Univ Ctr Computat Syst Biol Sch Math Sci Shanghai 200433 Peoples R China Fudan Univ Lab Math Nonlinear Sci Sch Math Sci Shanghai 200433 Peoples R China Fudan Univ Sch Comp Sci Key Lab Nonlinear Math Sci Sch Math Sci Shanghai 200433 Peoples R China

In this letter, we propose a new approach for the stability analysis of distributed continuous-time consensus algorithms in directed networks with time-dependent communication patterns. Instead of using a continuous-time Lyapunov function, we show how to analyze such a continuous-time algorithm by converting it to a discrete-time model. By using this method, we obtain a more general convergence result than existing ones. An example with numerical simulation is also provided to illustrate the theoretical results. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： distributed algorithms Multiagent systems Consensus Discontinuous Switching Almost sure convergence

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An Arrow-Hurwicz-Uzawa type flow as least squares solver for network linear equations

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AUTOMATICA 2019年 100卷 187-193页

作者： Liu, Yang Lageman, Christian Anderson, Brian D. O. Shi, Guodong Australian Natl Univ Res Sch Engn Coll Engn & Comp Sci Canberra ACT 0200 Australia Australian Natl Univ Res Sch Engn Canberra ACT 0200 Australia Univ Wurzburg Inst Math D-97070 Wurzburg Germany Hangzhou Dianzi Univ Hangzhou 310018 Zhejiang Peoples R China

We study the approach to obtaining least squares solutions to systems of linear algebraic equations over networks by using distributed algorithms. Each node has access to one of the linear equations and holds a dynamic state. The aim for the node states is to reach a consensus as a least squares solution of the linear equations by exchanging their states with neighbors over an underlying interaction graph. A continuous-time distributed least squares solver over networks is developed in the form of the famous Arrow-Hurwicz-Uzawa flow. A necessary and sufficient condition is established on the graph Laplacian for the continuous-time distributed algorithm to give the least squares solution in the limit, with an exponentially fast convergence rate. The feasibility of different fundamental graphs is discussed including path graph and random graph. Moreover, a discrete-time distributed algorithm is developed by Euler's method, converging exponentially to the least squares solution at the node states with suitable step size and graph conditions. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： distributed algorithms Dynamical systems Linear equations Least squares

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distributed Optimization for Weighted Vertex Cover via Heuristic Game Theoretic Learning

Distributed Optimization for Weighted Vertex Cover via Heuri...

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IEEE Conference on Decision and Control

作者： Changhao Sun Xiaochu Wang Huaxin Qiu Qian Chen Qingrui Zhou Qian Xuesen Laboratory of Space Technology China Academy of Space Technology Beijing China School of Automation Southeast University Nanjing China University of Wisconsin Madison Madison WI USA

ISBN: (数字)9781728174471

ISBN: (纸本)9781728174488

For the generation of higher-quality solutions to the distributed minimum weighted vertex cover (MWVC) problem, we propose a game theoretic learning algorithm by designing a weighted memory based rule. Being viewed as a rational player, each node in the network stochastically updates its action by following a probability distribution that is determined by neighborhood information including node degrees and weights. Within the framework of game theory, we prove that our method converges with probability 1 to Nash equilibria that correspond to near-optimal vertex cover solutions. Moreover, simulation results show that the memory length provides an additional freedom for solution efficiency improvement such that better system level objectives are more likely to be obtained by using a longer memory length. Comparison experiments with typical distributed algorithms demonstrate the superiority of the presented methodology to the state of the art.

关键词： Games Optimized production technology Nash equilibrium Optimization Heuristic algorithms distributed algorithms Sun

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distributed Observer Approach for Scalable Formation Control of Multi-Agent Network

Distributed Observer Approach for Scalable Formation Control...

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International Seminar on Intelligent Technology and Its Applications (ISITIA)

作者： Djati Wibowo Djamari Muhamad Rausyan Fikri Mechanical Engineering Study Program Sampoerna University Jakarta Indonesia Information System Study Program Sampoerna University Jakarta Indonesia

ISBN: (数字)9781728174136

ISBN: (纸本)9781728174143

This work studies formation control of Multi-Agent Systems (MASs) where its formation size is scalable via a scaling factor (scalable formation). Previous works on scalable formation are limited to either fixed undirected graph or fixed directed graph with p-rooted graph condition. This work proposes a novel distributed algorithm for scalable formation based on a distributed observer to estimate agents' positions. The novel algorithm results in a new matrix, a Laplacian matrix with additional diagonal terms, where the desired formation pattern is embedded in this diagonal terms. With the proposed algorithm, only spanning tree condition is needed as the necessary and sufficient condition to achieve the scalable formation. Numerical examples are shown to illustrate the proposed method.

关键词： Eigenvalues and eigenfunctions Observers distributed algorithms Laplace equations Standards Topology Nickel

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distributed Computation of Graph Matching in Multi-Agent Networks

Distributed Computation of Graph Matching in Multi-Agent Net...

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IEEE Conference on Decision and Control

作者： Quoc Van Tran Zhiyong Sun Brian D. O. Anderson Hyo-Sung Ahn School of Mechanical Engineering Gwangju Institute of Science and Technology Gwangju Republic of Korea Eindhoven University of Technology (TU/e) the Netherlands Research School of Electrical Energy and Materials Engineering Australian National University Australia the School of Automation Hangzhou Dianzi University Hangzhou China the Data61-CSIRO Canberra Australia

ISBN: (数字)9781728174471

ISBN: (纸本)9781728174488

This work investigates the distributed computation of the one-to-one vertex correspondences between two undirected and connected graphs, which is called graph matching, over multi-agent networks. Given two isomorphic and asymmetric graphs, there is a unique permutation matrix that maps the vertices in one graph to the vertices in the other. Based on a convex relaxation of graph matching in Aflalo et al. [1], we propose a distributed computation of graph matching as a distributed convex optimization problem subject to equality constraints and a global set constraint, using a network of multiple agents whose interaction graph is connected. Each agent in the network only knows one column of each of the adjacency matrices of the two graphs, and all agents collaboratively learn the graph matching by exchanging information with their neighbors. The proposed algorithm employs a projected primal-dual gradient method to handle equality constraints and a set constraint. Under the proposed algorithm, the agents' estimates of the permutation matrix converge to the optimal permutation globally and exponentially fast.

关键词： Symmetric matrices Optimization Pattern matching Convex functions distributed algorithms Two dimensional displays Sun

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