检索结果-内蒙古大学图书馆

distributed Power Control for Large Energy Harvesting Networks: A Multi-Agent Deep Reinforcement Learning Approach

IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING 2019年第4期5卷 1140-1154页

作者： Sharma, Mohit K. Zappone, Alessio Assaad, Mohamad Debbah, Merouane Vassilaras, Spyridon Univ Paris Saclay Cent Supelec F-91192 Gif Sur Yvette France Cent Supelec Lab Signaux & Syst F-91190 Gif Sur Yvette France Univ Cassino & Southern Lazio Dept Elect & Informat Engn I-03043 Cassino Italy Huawei France R&D Math & Algorithm Sci Lab F-92100 Paris France

In this paper, we develop a multi-agent reinforcement learning (MARL) framework to obtain online power control policies for a large energy harvesting (EH) multiple access channel, when only causal information about the EH process and wireless channel is available. In the proposed framework, we model the online power control problem as a discrete-time mean-field game (MFG), and analytically show that the MFG has a unique stationary solution. Next, we leverage the fictitious play property of the mean-field games, and the deep reinforcement learning technique to learn the stationary solution of the game, in a completely distributed fashion. We analytically show that the proposed procedure converges to the unique stationary solution of the MFG. This, in turn, ensures that the optimal policies can be learned in a completely distributed fashion. In order to benchmark the performance of the distributed policies, we also develop a deep neural network (DNN) based centralized as well as distributed online power control schemes. Our simulation results show the efficacy of the proposed power control policies. In particular, the DNN based centralized power control policies provide a very good performance for large EH networks for which the design of optimal policies is intractable using the conventional methods such as Markov decision processes. Further, performance of both the distributed policies is close to the throughput achieved by the centralized policies.

关键词： Artificial neural networks distributed algorithms energy harvesting learning (artificial intelligence) multi-agent systems multiple access

来源：评论

学校读者我要写书评

暂无评论

distributed Newton Method for Large-Scale Consensus Optimization

引用

IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2019年第10期64卷 3983-3994页

作者： Tutunov, Rasul Bou-Ammar, Haitham Jadbabaie, Ali Huawei Technol Res & Dev Shenzhen Peoples R China MIT Inst Data Syst & Soc 77 Massachusetts Ave Cambridge MA 02139 USA

In this paper, we propose a distributed Newton method for decenteralized optimization of large sums of convex functions. Our proposed method is based on creating a set of separable finite sum minimization problems by utilizing a decomposition technique known as Global Consensus that distributes the computation across nodes of a graph and enforces a consensus constraint among the separated variables. The key idea is to exploit the sparsity of the dual Hessian and recast the computation of the Newton step as one of the efficiently solving symmetric diagonally dominant linear equations. We show that our method outperforms the state-of-the-art algorithms, including ADMM. We validate our algorithm both theoretically and empirically. On the theory side, we demonstrate that our algorithm exhibits superlinear convergence within a neighborhood of optimality. Empirically, we show the superiority of this new method on a variety of large-scale optimization problems. The proposed approach is scalable to large problems and has a low communication overhead.

关键词： Convergence distributed algorithms

来源：评论

学校读者我要写书评

暂无评论

A distributed Evolutionary algorithm for detecting minimum vertex cuts for wireless ad hoc and sensor networks

引用

JOURNAL OF NETWORK AND COMPUTER APPLICATIONS 2019年第Feb.期127卷 70-81页

作者： Dagdeviren, Orhan Akram, Vahid Khalilpour Farzan, Ali Ege Univ Int Comp Inst Izmir Turkey Islamic Azad Univ Comp Dept Shabestar Iran

A minimum vertex cut (MVC) of a graph G is the smallest subset of vertices whose removal creates at least two disconnected group of other vertices. Detecting nodes in MVCs in wireless ad hoc and sensor networks (WASNs) provides valuable information about their robustness and critical parts. There is a wide variety of central algorithms that find or estimate MVCs of graphs, but to the best of our knowledge the existing distributed algorithms can only estimate the cardinality of MVCs, or k, from local neighborhood information. Regardless of the fact that MVCs remain unknown in these algorithms, local estimation of k may produce wrong values, far from the real k. We propose a distributed algorithm, which uses an adapted meta heuristic method, to detect the nodes in MVCs. In the proposed algorithm, all nodes find their available paths to the sink (root node) and determine the minimum subset of nodes that their failure disconnects all detected paths. The smallest detected sets by the nodes will be MVCs of the WASN. Besides finding the union of MVCs with up to 89% average accuracy, the testbed and simulation results show that the correct detection ratio of k in the proposed algorithm is up to 37% more than the existing distributed algorithms.

关键词： Minimum vertex cut Imperialist competitive algorithm Evolutionary algorithms distributed algorithms k-connectivity Fault tolerance Reliability Wireless ad hoc and sensor networks

来源：评论

学校读者我要写书评

暂无评论

distributed Clustering of Text Collections

引用

IEEE ACCESS 2019年 7卷 155671-155685页

作者： Zamora, Juan Allende-Cid, Hector Mendoza, Marcelo Pontificia Univ Catolica Valparaiso Inst Estadist Valparaiso 2340023 Chile Pontificia Univ Catolica Valparaiso Escuela Ingn Informat Valparaiso 2362807 Chile Univ Tecn Federico Santa Maria Ctr Cient & Tecnol Valparaiso Valparaiso 2390123 Chile

Current data processing tasks require efficient approaches capable of dealing with large databases. A promising strategy consists in distributing the data along with several computers that partially solve the undertaken problem. Finally, these partial answers are integrated to obtain a final solution. We introduce distributed shared nearest neighbors (D-SNN), a novel clustering algorithm that work with disjoint partitions of data. Our algorithm produces a global clustering solution that achieves a competitive performance regarding centralized approaches. The algorithm works effectively with high dimensional data, being advisable for document clustering tasks. Experimental results over five data sets show that our proposal is competitive in terms of quality performance measures when compared to state of the art methods.

关键词： Clustering algorithms distributed databases Partitioning algorithms Task analysis Computers Parallel processing Approximation algorithms distributed algorithms distributed text clustering high dimensional data

来源：评论

学校读者我要写书评

暂无评论

Multi-Agent System Based distributed Pattern Search Algorithm for Non-Convex Economic Load Dispatch in Smart Grid

引用

IEEE TRANSACTIONS ON POWER SYSTEMS 2019年第3期34卷 2093-2102页

作者： Li, Fangyuan Qin, Jiahu Kang, Yu Univ Sci & Technol China Dept Automat Hefei 230027 Anhui Peoples R China Univ Sci & Technol China Dept Automat State Key Lab Fire Sci Hefei 230027 Anhui Peoples R China Univ Sci & Technol China Inst Adv Technol Hefei 230027 Anhui Peoples R China Chinese Acad Sci Key Lab Technol Geospatial Informat Proc & Applic Beijing 100190 Peoples R China

Since generation units usually subject to valve point effects and there is a trend of ever-growing number of distributed energy sources, distributed optimization algorithms for non-convex economic load dispatch are more desirable than the centralized ones. In this paper, a distributed pattern search algorithm (DPSA) for non-convex economic dispatch is developed. To develop such an algorithm, a flooding-based topology discovery algorithm (FBTDA) is proposed first. Theoretic analysis shows that the FBTDA algorithm converges in the least number of iterations compared with existing methods. Then, the DPSA algorithm is developed by integrating the original pattern search algorithm and the FBTDA algorithm under the framework of multi-agent systems. The DPSA algorithm has a rather weak requirement on the communication topology. Rigorous convergence analysis is provided as opposed to previous literatures where convergence property is often not investigated. The correctness and efficiency of the proposed algorithms are verified by numerical simulations, which also show that the DPSA algorithm can improve performance by actively choosing communication topology and integrating other global search methods. Comparisons with traditional methods show that besides the potential benefits arising from the absence of central nodes, the DPSA algorithm has comparable performance to these methods.

关键词： Convergence distributed algorithms multi-agent systems power generation dispatch

来源：评论

学校读者我要写书评

暂无评论

A distributed Algorithm for Least Squares Solutions

引用

IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2019年第10期64卷 4217-4222页

作者： Wang, Xuan Zhou, Jingqiu Mou, Shaoshuai Corless, Martin J. Purdue Univ Sch Aeronaut & Astronaut W Lafayette IN 47906 USA

In this technical note, a distributed algorithm is proposed for multiagent networks to achieve a least squares solution of a system of linear equations, in which each agent only knows part of the overall equations and communicates only with its nearby neighbors. The proposed algorithm is discrete time but does not involve small or time-varying step sizes. Given that the network is fixed, connected, and undirected, the proposed algorithm enables all agents in the network to achieve exponentially fast the same least squares solution;this is validated by simulations.

关键词： distributed algorithms least squares solutions linear equations multiagent networks

来源：评论

学校读者我要写书评

暂无评论

Survey Propagation for Cell-Free Massive MIMO Pilot Assignment

Survey Propagation for Cell-Free Massive MIMO Pilot Assignme...

引用

IEEE Globecom Workshops

作者： Sunho Kim Hong Ki Kim Sang Hyun Lee School of Electrical Engineering Korea University Seoul Korea

ISBN: (纸本)9781665459761

This work develops a survey propagation approach to distributed pilot assignment (PA) optimization in cell-free massive multiple-input multiple-output networks. The reuse of pilot signals among multiple links incurs the pilot contamination, thereby degrading the system performance. For sustainable management of pilot sequences, the PA operation policy can be formulated in a combinatorial way. To avoid large-scale computational loads, the resulting optimization task is approached in a novel distributed framework of survey propagation, which has been originally developed to address interacting particle systems in physics. A developed algorithm demonstrates outperforming behaviors over existing schemes with respect to the overall network throughput.

关键词： System performance Partial transmit sequences Massive MIMO Throughput MIMO Task analysis distributed algorithms

来源：评论

学校读者我要写书评

暂无评论

Regular Topology Formation Based on Artificial Forces for distributed Mobile Robotic Networks

引用

IEEE TRANSACTIONS ON MOBILE COMPUTING 2019年第10期18卷 2415-2429页

作者： Zhao, Haitao Wei, Jibo Huang, Shengchun Zhou, Li Tang, Qi Natl Univ Def Technol Coll Elect Sci Changsha 410073 Hunan Peoples R China

The distributed mobile robotic network consists of a group of mobile nodes, such as mobile sensors, unmanned vehicles, unmanned submarines, unmanned air vehicles, or mobile robots. The mobile robotic network keeping a regular topology can utilize efficient network protocols and is also promising in many application scenarios. We propose a distributed algorithm that controls multiple distributed robotic nodes to form regular topology, including straight line, ring, triangular lattice, and square lattice. Our algorithm generates artificial forces, including the attractive force towards a reference point to gather the distributed nodes, the repulsive force from neighboring nodes to keep the desirable distance among them, the formation force to form a specific shape, and the obstacle avoidance force to avoid possible obstacles, such that each node simply follows the resultant force to move. The algorithm works in a fully distributed manner, converges fast, and is easy to deploy, requiring only one-hop local network geometry information. And, it is effective under both 2D and 3D scenarios. A computer demo is developed to demonstrate the effectiveness of the algorithm for large numbers of robotic nodes.

关键词： Topology formation mobile robotic networks artificial forces distributed algorithms

来源：评论

学校读者我要写书评

暂无评论

distributed Nash equilibrium seeking under partial-decision information via the alternating direction method of multipliers

引用

AUTOMATICA 2019年 103卷 27-35页

作者： Salehisadaghiani, Farzad Shi, Wei Pavel, Lacra Univ Toronto Dept Elect & Comp Engn Toronto ON M5S 3G4 Canada Arizona State Univ Sch Elect Comp & Energy Engn Tempe AZ 85287 USA

In this paper, we consider the problem of finding a Nash equilibrium in a multi-player game over generally connected networks. This model differs from a conventional setting in that players have partial information on the actions of their opponents and the communication graph is not necessarily the same as the players' cost dependency graph. We develop a relatively fast algorithm within the framework of inexact-ADMM, based on local information exchange between the players. We prove its convergence to Nash equilibrium for fixed step-sizes and analyse its convergence rate. Numerical simulations illustrate its benefits when compared to a consensus-based gradient type algorithm with diminishing step-sizes. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Game theory over networks distributed algorithms Noncooperative games Communication graph

来源：评论

学校读者我要写书评

暂无评论

A Real-Time and Fully distributed Approach to Motion Planning for Multirobot Systems

引用

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2019年第12期49卷 2636-2650页

作者： Zhou, Yuan Hu, Hesuan Liu, Yang Lin, Shang-Wei Ding, Zuohua Nanyang Technol Univ Sch Comp Sci & Engn Coll Engn Singapore 639798 Singapore Xidian Univ Sch Electromech Engn Xian 710071 Shaanxi Peoples R China Xi An Jiao Tong Univ State Key Lab Mfg Syst Engn Xian 710054 Shaanxi Peoples R China Zhejiang Sci Tech Univ Sch Informat Sci Hangzhou 310018 Zhejiang Peoples R China

Motion planning is one of the most critical problems in multirobot systems. The basic target is to generate a collision-free trajectory for each robot from its initial position to the target position. In this paper, we study the trajectory planning for the multirobot systems operating in unstructured and changing environments. Each robot is equipped with some sensors of limited sensing ranges. We propose a fully distributed approach to planning trajectories for such systems. It combines the model predictive control (MPC) strategy and the incremental sequential convex programming (iSCP) method. The MPC framework is applied to detect the local running environment real-timely with the concept of receding horizon. For each robot, a nonlinear programming is built in its current prediction horizon. To construct its own optimization problem, a robot first needs to communicate with its neighbors to retrieve their current states. Then, the robot predicts the neighbors' future positions in the current horizon and constructs the problem without waiting for the prediction information from its neighbors. At last, each robot solves its problem independently via the iSCP method such that the robot can move autonomously. The proposed method is polynomial in its computational complexity.

关键词： distributed algorithms motion planning multirobot systems trajectory optimization

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：