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检索条件"主题词=distributed algorithms"

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Fixed-Time distributed Algorithm for Economic Dispatch in Smart Grid

Fixed-Time Distributed Algorithm for Economic Dispatch in Sm...

引用

Chinese Automation Congress (CAC)

作者： Hui Li Ying-Jiang Zhou Guo-Ping Jiang Sheng-Yu Ge Shuai Zhou Department of Automation and Artificial Intelligence Nanjing University of Posts and Telecommunications Nanjing P. R. China

The power dispatch is the key to guarantee the operation stability of power grid, with development of society, Along with societys development progress, scholars begin to realize gradually, the traditional economic dispatching method already could not meet the needs. Under this background, distributed economic dispatch has received more and more attention from scholars. This paper proposes a distributed economic dispatch algorithm, and this algorithm can realize fixed-time convergence and minimize the total system cost for economic dispatch on the prerequisite of the balance between demand side and supply side. Under the fixed-time stability theory, when the initial states is bounded, the fixed-time algorithm can be proved. Finally, some cases are simulated to illustrate efficiency of the algorithm we proposed.

关键词： Economics Smart grids Generators distributed algorithms Convergence Laplace equations Power system stability

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distributed Landmark Placement in P2P Networks 26

Distributed Landmark Placement in P2P Networks

引用

26th IEEE Signal Processing and Communications Applications Conference (SIU)

作者： Boshrooyeh, Sanaz Taheri Ozkasap, Oznur Akgun, Baris Koc Univ Dept Comp Engn Istanbul Turkey

ISBN: (纸本)9781538615010

Peer-to-peer (P2P) paradigm is a promising way to provide services to the masses for a very low cost, and hence, P2P services have been gaining significant attention. Since P2P services usually operate over their users' resources, without using central servers, their performance is becoming of interest to researchers. Several existing solutions rely on supernodes, called landmarks, to enhance system performance. The landmarks are placed manually based on the density and the distribution of the nodes in the corresponding P2P network, and landmark locations are presumed to be determined before system setup. However, this assumption is not realistic since, in a P2P system, no global view about the peers' locations exists. Hence, the best landmark locations would not be known a priori. We propose a family of distributed landmark placement algorithms, called DLP, to address this issue. We implement four versions of the DLP family and evaluate their landmark placements in a simulation environment. We define two performance metrics to assess their performance as compared to manually placed landmarks. Our results show that the DLP algorithms can generate landmark locations that are on par with the manual placement and significantly reduce the landmark-to-peer latencies.

关键词： P2P DHT Skip Graph Identifier Landmark placement distributed algorithms

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A distributed Algorithm with Scalar States for Solving Linear Equations 57

A Distributed Algorithm with Scalar States for Solving Linea...

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57th IEEE Conference on Decision and Control (CDC)

作者： Wang, Xuan Mou, Shaoshuai Anderson, Brian. D. O. Purdue Univ Sch Aeronaut & Astronaut W Lafayette IN 47906 USA Hangzhou Dianzi Univ Hangzhou Zhejiang Peoples R China Australian Natl Univ Canberra ACT 2600 Australia CSIRO Data 61 Canberra ACT 2600 Australia

ISBN: (纸本)9781538613955

Based on a combination of consensus and conservation, the paper develops a distributed update for solving linear equations by multi-agent networks, in which each agent only knows just a small part of the overall equation and can only communicate with its nearby neighbors. In the proposed distributed update, each agent knows only two scalar entries of the defining matrix of the overall equation and controls just two scalar states. Given the underlying networks to be connected and undirected, the proposed distributed update enables agents to collaboratively achieve a solution to the overall equation. Analytical proof is provided for the exponential convergence of the proposed update, which is also validated by numerical simulations.

关键词： Mathematical model Eigenvalues and eigenfunctions Convergence distributed algorithms Laplace equations Conferences Numerical simulation

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distributed Algorithm for the Network Size Estimation: Blended Dynamics Approach 57

Distributed Algorithm for the Network Size Estimation: Blend...

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57th IEEE Conference on Decision and Control (CDC)

作者： Lee, Donggil Lee, Seungjoon Kim, Taekyoo Shim, Hyungbo Seoul Natl Univ Dept Elect & Comp Engn ASRI Seoul South Korea

ISBN: (纸本)9781538613955

This paper presents a distributed algorithm for the network size estimation problem. The problem is to find the total number of nodes in the network. The proposed algorithm utilizes the continuous-time dynamics for achieving synchronization, which provides a way to assign each element of the equilibrium point of the dynamics close to the network size. The algorithm guarantees that each node directly estimates the total number of nodes in the network. Moreover, the network size can be estimated regardless of initial condition. We also derive the stopping criteria of the algorithm and extend the result to the case where the network varies intermittently with time.

关键词： Heuristic algorithms distributed algorithms Estimation Couplings Symmetric matrices Vehicle dynamics Synchronization

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A distributed Stochastic Gradient Tracking Method 57

A Distributed Stochastic Gradient Tracking Method

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57th IEEE Conference on Decision and Control (CDC)

作者： Pu, Shi Nedic, Angelia Arizona State Univ Sch Elect Comp & Energy Engn Tempe AZ 85287 USA

ISBN: (纸本)9781538613955

In this paper, we study the problem of distributed multi-agent optimization over a network, where each agent possesses a local cost function that is smooth and strongly convex. The global objective is to find a common solution that minimizes the average of all cost functions. Assuming agents only have access to unbiased estimates of the gradients of their local cost functions, we consider a distributed stochastic gradient tracking method. We show that, in expectation, the iterates generated by each agent are attracted to a neighborhood of the optimal solution, where they accumulate exponentially fast (under a constant step size choice). More importantly, the limiting (expected) error bounds on the distance of the iterates from the optimal solution decrease with the network size, which is a comparable performance to a centralized stochastic gradient algorithm. Numerical examples further demonstrate the effectiveness of the method.

关键词： Stochastic processes Convergence Cost function Radio frequency Limiting distributed algorithms

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Energy-Aware distributed Edge Domination of Multilayer Networks

Energy-Aware Distributed Edge Domination of Multilayer Netwo...

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American Control Conference

作者： Dimitrios Papakostas Soheil Eshghi Dimitrios Katsaros Leandros Tassiulas University of Thessaly Volos Greece Yale Institute of Network Science (YINS) Yale University New Haven CT USA Visiting assistant professor Yale University

ISBN: (纸本)9781538679012;9781538679265

Monitoring and maintaining communications in a multilayer ad hoc wireless network requires a stable communication overlay. Such monitoring should be resilient, avoiding reliance on a single (or a few) layers, and energy-aware, not being vulnerable to the exhaustion of available energy in a single network element. Thus, there is possibly a trade-off between overlay size, interlayer connectivity, and the energy distribution within the overlay. In this paper, we present three distributed energy-aware multilayer connected edge dominating set algorithms, show how they manage such trade-offs in practical scenarios, and show that CCEDS, a pruned centrality-based distributed algorithm, has the best performance.

关键词： Overlay multilayers energy distribution network element Mobile ad hoc networks distributed algorithms available energy Authoritarianism optimum performance Edge of a figure or solid Exhaustion Vulnerable Distribute Wireless networks Communication Research

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distributed Learning over Time-Varying Graphs with Adversarial Agents

Distributed Learning over Time-Varying Graphs with Adversari...

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International Conference on Information Fusion

作者： Pooja Vyavahare Lili Su Nitin H. Vaidya Indian Institute of Technology Tirupati Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Georgetown University

ISBN: (数字)9780996452786

ISBN: (纸本)9781728118406

In this work, we study the problem of non-Bayesian learning in time-varying (dynamic) networks when there are some adversarial (faulty) agents in the network. The set of faulty agents is fixed across time. The connectivity graph of the network is changing at each time step and is unknown to the agents. In every time step, each non-faulty agent collects partial information about an unknown state of the environment. Each non-faulty agent tries to estimate the true state of the environment by iteratively sharing information with its neighbors at each time step. We first present an analysis of a distributed algorithm in static communication network with faulty agents which does not require the network to achieve consensus. Existing algorithms in this setting require that all non-faulty agents in the network should be able to achieve consensus via local information exchange. We then extend this analysis to dynamic networks with relaxed network condition. We show that if every non-faulty agent can receive enough information (via iteratively communicating with neighbors) to differentiate the true state of the world from other possible states then it can indeed learn the true state.

关键词： Communication networks Graph theory Multi-agent systems Network theory (graphs) Time-varying systems distributed algorithms

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distributed Energy-Adaptive Aggregation Scheduling with Coverage Guarantee For Battery-Free Wireless Sensor Networks

Distributed Energy-Adaptive Aggregation Scheduling with Cove...

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IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Kunyi Chen Hong Gao Zhipeng Cai Quan Chen Jianzhong Li Harbin Institute of Technology Georgia State University Guangdong University of Technology

Thanks to the recent advances in energy-harvesting devices, nodes equipped with such devices are produced and enable Wireless Sensor Networks (WSNs) to be energy self-sustainable. Such networks are named as Battery-Free WSNs (BF-WSNs). Data aggregation is an essential operation in WSNs, and the Minimum Latency Aggregation Scheduling (MLAS) problem which seeks a collision-free aggregation scheduling with the minimum latency has been well studied in Battery-Powered WSNs (BP-WSN). In BP-WSNs, latency is mainly caused by the time overhead in collision-avoiding. However, the time-consumption for node recharging is the main cause of latency in BF-WSNs. Moreover, the collisions are time-independent while the recharge rate is time-varying. Therefore, the previous algorithms are not suitable for BF-WSNs. In addition, if aggregating data from all nodes, the latency would be determined by the node with the lowest recharge rate. Thus, we propose to aggregate a subset of nodes which can meet the given coverage quality requirement. Meanwhile, the aggregation tree and scheduling strategy should be adaptive to the current energy condition. We formulate this problem and propose a distributed algorithm which can select nodes adaptively according to their energy condition and schedule these nodes to achieve the minimum latency, simultaneously. To the best of our knowledge, it is the first distributed algorithm to solve the MLAS problem with coverage guarantee in BF-WSNs. The simulation results verify that our algorithm can reduce aggregation latency effectively, especially in bad energy condition.

关键词： Wireless sensor networks Schedules Monitoring Energy consumption Interference distributed algorithms Data aggregation

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Building Temperature Control: A distributed Escort Dynamical approach

Building Temperature Control: A Distributed Escort Dynamical...

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IEEE International Conference on Power and Energy Systems (ICPES)

作者： M. Sawant J. Moyalan J. Koonamparampath A. Sheikh S. Wagh N. Singh Electrical Engineering Department Veermata Jijabai Technological Institute Mumbai India

ISBN: (数字)9781728126586

ISBN: (纸本)9781728126593

The constrained multi-agent optimization problem of building temperature control (BTC) is addressed in the framework of distributed resource allocation (DRA) using evolutionary game theory (EGT). The relationship between limited resource availability of DRA problem and constant population size requirement is established to devise population dynamic based control law. The BTC plant dynamics interconnected with the control dynamics are evaluated in the context of convergence to the rest point in terms of output consensus for dynamical systems. Furthermore, mitigating the expectation dependency of escort dynamical model of EGT, a DRA protocol is proposed referred to as distributed escort dynamics (DED). It ensures the satisfaction of global resource bound along with the local resource bounds on individual control parameters which is not the case for general dynamics such as replicator dynamics, logit dynamics, etc. referred to as classical models. The control action devised adopting DED approach is shown to provide smooth trajectory tracking along with the low start-up transience when compared with distributed interior point (DIP) method.

关键词： Consensus problems distributed algorithm Escort dynamics Graph theory Resource allocation distributed algorithms Resource utilization Graph theory control dynamics control action management of resources Resource availability Temperature control dynamics Distribute DED AATF Gene BTC gene control law

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Convergence Rate of distributed Subgradient Methods under Communication Delays

Convergence Rate of Distributed Subgradient Methods under Co...

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American Control Conference

作者： Doan, Thinh T. Beck, Carolyn L. Srikant, R. Univ Illinois Coordinated Sci Lab Urbana IL 61801 USA

ISBN: (纸本)9781538654286

Motivated by broad applications in computer science and engineering, we study distributed algorithms for optimization problems over a network of nodes, where the goal is to optimize a global objective composed of a sum of local functions. In this paper, we consider a popular distributed gradient-based consensus algorithm, which only requires local computation and communication. A significant problem in this area is to analyze the convergence rate of such algorithms in the presence of communication delays that are inevitable in distributed systems. Our main contribution is to obtain an upper bound on the rate of convergence of the algorithm as a function of the network size, topology, and the inter-node communication delays.

关键词： Delays Convergence Gradient methods distributed algorithms Program processors Linear programming"

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