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检索条件"主题词=distributed algorithms"

共 6250 条记录，以下是961-970 订阅

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Agent-Based Triangle Counting and Its Applications in Anonymous Graphs 24

Agent-Based Triangle Counting and Its Applications in Anonym...

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Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems

作者： Prabhat Kumar Chand Apurba Das Anisur Rahaman Molla Indian Statistical Institute Kolkata India BITS Pilani Hyderabad India

ISBN: (纸本)9798400704864

Triangle counting in graphs is a fundamental problem with a diverse application domain. In this paper, we propose a solution to the triangle counting problem in an anonymous graph using autonomous mobile agents. We further use the triangle count to address the Truss Decomposition problem which involves finding maximal sub-graphs with strong interconnections. Truss decomposition helps in identifying maximal, highly interconnected sub-graphs, or trusses, within a network. Additionally, the triangle count is also used to compute two important metrics - Triangle Centrality and Local Clustering Coefficient for the nodes of the graph. Our goal is to devise algorithms that effectively solve these problems minimizing both the overall time complexity and the memory usage at each agent.

关键词： $k$-truss distributed algorithms local clustering coefficient mobile agents network algorithms space complexity time complexity triangle centrality triangle counting truss decomposition

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Optimal Sizing and Scheduling Systems for Fast Charging Stations Participated in Electricity Market

Optimal Sizing and Scheduling Systems for Fast Charging Stat...

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IEEE General Meeting Power& Energy Society

作者： Xuan Jiang Qianwen Xu Division of Electric Power and Energy Systems KTH Royal Institute of Technology Stockholm Sweden

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

The popularity of electrical vehicles (EVs) has led to a significant increase in the demand for fast charging stations (FCSs). To save energy and increase revenue, the planning and scheduling systems of fast charging stations are necessary. In this paper, a two-stage iteration method is proposed to solve the combined sizing and scheduling problem of FCSs to achieve overall minimized cost and maximized flexibility under uncertainties of EV demand, PV generation, and basic loads. Furthermore, an Alternating Direction Method Of Multipliers (ADMM) based distributed algorithm is proposed to deal with computational complexity and reduce the computation burden. The robust optimization method is used to deal with the uncertainties of EV demands, solar radiation, and basic loads. The method considered the interaction between planning and scheduling with a distributed solution, thus achieving overall minimized cost and low computation burden.

关键词： Uncertainty Costs Processor scheduling Optimization methods Scheduling Convex functions Fast charging Planning Solar radiation distributed algorithms

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Pair-Covering Codes

Pair-Covering Codes

引用

IEEE International Symposium on Information Theory

作者： Avital Boruchovsky Tuvi Etzion Eitan Yaakobi Department of Computer Science Technion-Israel Institute of Technology Haifa Israel

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

Motivated by distributed algorithms for fuzzy joins, the concept of pair-covering ${}^{\prime\prime}$ codes is defined. This definition is a generalization of the well-known concept of covering codes. Basic properties and bounds for the pair-covering codes with comparison to the associated properties and bounds for covering codes, are provided. In particular, the sphere covering bound and normal codes are generalized.

关键词： Error correction codes distributed algorithms

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A distributed Algorithm with a Modified Quantization Radius Under Limited Communication

A Distributed Algorithm with a Modified Quantization Radius ...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Boya Zhang Zhujun Cao Tingting Wang Enbin Song Department of Mathematics Sichuan University Chengdu China China Aerospace Science and Technology Corporation Sichuan Aerospace Research Institute of Electronic Equipment Chengdu China

ISBN: (纸本)9781665465373

distributed optimization is a very significant approach with applications in control theory and lots of related fields, as it is high fault-tolerant and extremely efficient compared with centralized optimization. In distributed optimization, quantization is a communication technique, which exchanges information bits more reliably at the expense of a lower communication rate. In this paper, we put forward a distributed quantization algorithm to handle a class of problems with the sum of multiple objective functions. Particularly, we design a customized quantization radius, which preserves a fast convergence rate while saving more bits of information exchange. The numerical experiments demonstrate the high efficiency of our algorithm.

关键词： Fault tolerance Quantization (signal) Fault tolerant systems Reliability theory Linear programming Control theory distributed algorithms

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Coordinating Cross-robot Resource for Task Allocation with Decentralized Cooperative Genetic Algorithm

Coordinating Cross-robot Resource for Task Allocation with D...

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IEEE International Conference on Unmanned Systems (ICUS)

作者： Yifan Wang Jiaxing Mao Yu Yang China State Shipbuilding Corp. Ltd. Systems Engineering Research Institute Beijing China

ISBN: (数字)9798350384185

ISBN: (纸本)9798350384192

This paper proposes a decentralized cooperative genetic algorithm (DCGA) to address the cross-robot resource allocation problem in leaderless multi-robot systems (MRS), where each agent is only capable of making local decisions based on local information. Inspired by the fundamental concept of divide-and-conquer in co-evolution mechanisms, the DCGA alternates between two steps: local evolution and global negotiation, within each robot. Our problem formulation enables the algorithm to effectively manage complex cross-robot constraints, which are often challenging in distributed algorithms. Unlike parallelized algorithms that necessitate agents to possess global decision-making capabilities, the DCGA facilitates the seamless integration of agents into multi-agent systems (MAS) by merely incorporating information interaction logic. Experimental results demonstrate that the DCGA is competitive in terms of optimization speed and yields superior solutions compared to centralized genetic algorithms (CGA). Furthermore, it exhibits adaptability to network latency in wireless environments.

关键词： Wireless communication Robot kinematics Decision making Resource management Multi-robot systems Logic distributed algorithms Optimization Genetic algorithms Multi-agent systems

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Gossip Based Consensus Algorithm for Multi-Agent Systems

Gossip Based Consensus Algorithm for Multi-Agent Systems

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Innovative Approaches in Smart Technologies (ISAS), International Symposium on

作者： Mutullah Eşer Asım Egemen Yılmaz Electrical and Electronics Engineering Ankara University Ankara Türkiye

ISBN: (数字)9798331540104

ISBN: (纸本)9798331540111

Multi-agent systems presently find extensive applicability across diverse domains. Central to these applications is the imperative for agents to exchange information regarding their experiences, knowledge, and actions. distributed algorithms, denoting algorithms employed by multiple agents within a system to collaboratively execute a particular task, play a pivotal role. Within multi-agent systems, these algorithms facilitate the coordination of agents that are typically autonomous and possess decision-making capabilities. Given the diverse communication graph structures and communication challenges inherent in multi-agent systems employing distributed algorithms, agents necessitate a consensus phase. Conversely, the implementation of distributed algorithms within graphs featuring a substantial number of edges can exert significant strain on the limited resources of wireless nodes. This study proposes a gossip algorithm as a viable solution to the requirement for consensus among agents engaged in decentralized decision-making within multi-agent systems. The suggested algorithm reduce the graph through its scoring structure and fosters consensus among agents via the ranked gossip structure constructed upon this graph. Through simulation studies, the feasibility and effectiveness of the proposed algorithm across varied graph structures are demonstrated.

关键词： Wireless communication Decision making Consensus algorithm distributed algorithms Multi-agent systems Strain

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Maximizing the Total Utility of Requesters in Crowdsourcing

Maximizing the Total Utility of Requesters in Crowdsourcing

引用

High Performance and Smart Computing (HPSC), IEEE International Conference on

作者： Xiao Chen Department of Computer Science Texas State University San Marcos TX

ISBN: (数字)9798350389463

ISBN: (纸本)9798350389470

Crowdsourcing coordinates a large group of workers online to do small tasks published by requesters on a crowd-sourcing platform. In the literature, the model used by many papers assumes that one task is given to and completed by one worker only. In this paper, we consider a model that extends this model in space and time. Based on our model, we formulate an optimization problem from the perspective of the requesters that maximizes the utility of all the requesters subject to the constraint that the total workload given to a worker should not exceed his capability. We then provide a solution to the problem and design distributed algorithms for the requesters and the workers to interact with each other in multiple rounds. After that, we give a concrete example to explain the solution and the algorithms. Then, we discuss the convergence speed of our algorithms using different methods. Finally, we conduct simulations to compare these convergence methods and draw conclusions.

关键词： Crowdsourcing Computational modeling Task analysis distributed algorithms Optimization Convergence

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Multi-agent Target Position Estimation Using Bearing-only Measurements via Spatial Excitation

Multi-agent Target Position Estimation Using Bearing-only Me...

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American Control Conference (ACC)

作者： Soojeong Hyeon Iman Shames Hyungbo Shim Department of Electrical and Computer Engineering ASRI Seoul National University Korea Australian National University Acton Australia

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper solves the problem of estimating a single target position by a group of agents in two-dimensional space. Each agent is assumed to know its own position and to measure only the bearing to the target. We develop a distributed estimation scheme that processes individual bearing measurements by utilizing continuous-time dynamics with communication among the agents. Under the assumption of connectivity on the communication graph, it is shown that, even if each bearing measurement does not satisfy the persistency of excitation condition, each agent is able to estimate the target position provided that the agents are properly positioned. We examine this condition in terms of spatial excitation and its relationship with geometric configuration of the agents. Additionally, we analyze the convergence rate of the estimation error. Simulation results are provided to illustrate the performance of the proposed estimator.

关键词： Geometry Couplings Estimation error Simulation Position measurement distributed algorithms Convergence

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Poster: Green Network Optimization with Multi-Agent Reinforcement Learning: Work in Progress

Poster: Green Network Optimization with Multi-Agent Reinforc...

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IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social Computing (CPSCom) Green Computing and Communications (GreenCom)

作者： Vladimir Marbukh National Institute of Standards & Technology Gaithersburg MD

ISBN: (数字)9798350351637

ISBN: (纸本)9798350351644

This paper proposes a distributed Green Network Optimization (GNO) with Multi-Agent Reinforcement Learning (MARL). GNO-MARL combines: (a) Network Utility Maximization (NUM) based network management, given the capacity constraints, on a “fast” time scale, and (b) network dimensioning which balances the maximal network utility with the “carbon cost” of the transmissions on “slower” time scales. Inherent non-convexity of the GNO due to dominance of the idle power in network devices, including routers, makes exact solution of the GNO even by centralized algorithms for realistic size networks intractable. It is known that distributed algorithms may introduce additional to the duality gap loss in the performance due to oscillatory instability. We advocate that this additional loss may be significantly reduced or even eliminated with MARL. This possibility is based on properties of Lagrange multipliers and suggested by known results on reducing the corresponding additional loss in network performance.

关键词： Performance evaluation Social computing Costs Reinforcement learning distributed algorithms Carbon Optimization

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Near-Optimal Deterministic Network Decomposition and Ruling Set, and Improved MIS

Near-Optimal Deterministic Network Decomposition and Ruling ...

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Annual IEEE Symposium on Foundations of Computer Science

作者： Mohsen Ghaffari Christoph Grunau MIT Cambridge USA ETH Zurich Zurich Switzerland

ISBN: (数字)9798331516741

ISBN: (纸本)9798331516758

This paper improves and in two cases nearly settles, up to logarithmically lower order factors, the deterministic complexity of some of the most central problems in distributed graph algorithms, which have been studied for over three decades: • Near-Optimal Network Decomposition: We present a deterministic distributed algorithm that computes a network decomposition in $\tilde{O}(\log^distributed algorithmsn)$ rounds with $O(\log n)$ diameter and $O(\log n)$ colors. This round complexity is near-optimal in the following sense: even given an ideal network decomposition, using it (in the standard way) requires round complexity equal to the product of diameter and number of colors, and that is known to be $\tilde \Omega(\log^distributed algorithmsn)$ . We find this near-optimality remarkable, considering the rarity of optimal deterministic distributed algorithms and that for network decomposition, even the first polylogarithmic round algorithm was achieved only recently, by Rozhon and Ghaffari [STOC 2020], after three decades. • Near-Optimal Ruling Set: We present a deterministic distributed algorithm that computes an O(log log n) ruling set—i.e., an independent set such that each node is within its O(log log n) distance—in O(log n) rounds. This is an exponential improvement on the O(log n) ruling set of Awerbuch, Goldberg, Luby, and Plotkin [FOCS'89], while almost matching their O(log n) round complexity. Our result's round complexity nearly matches the (log n) lower bound of Balliu, Brandt, Kuhn, and Olivetti [STOC 2022] that holds for any poly(log log n) ruling set. • Improved Maximal Independent Set (MIS): We present a deterministic distributed algorithm for computing an MIS in $\tilde{O}(\log^{5/3}n)$ rounds. This improves on the $\tilde{O}(\log^distributed algorithmsn)$ complexity achieved by Ghaffari and Grunau [STOC 2023] and breaks the log-squared barrier necessary for any method based on network decomposition. By known reductions, the $\tilde{O}(\log^{5/3}n)$ round complexity also applies

关键词： Computer science Costs Color Complexity theory distributed algorithms Standards

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