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gossip algorithms for Computing U-statistics

IFAC Proceedings Volumes 2009年第20期42卷 48-53页

作者： Kristiaan Pelckmans Johan A.K. Suykens Division of Systems and Control Department of Information Technology Uppsala University SE-751 05 Uppsala Sweden KULeuven - ESAT - SCD/SISTA 3001 Leuven Belgium

This manuscript studies two ‘randomized gossip’ algorithms for computing a U -statistic over a weighted, (un)directed graph. We propose algorithms U 1- gossip and U 2- gossip and derive exponential convergence to a global consensus. The proofs rely on a convergence result for Markov chains and on a probabilistic concentration inequality.

关键词： gossip algorithm U -statistics Markov chains Concentration inequality

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A gossip Method for Optimal Consensus on a Binary State From Binary Actions

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IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING 2013年第2期7卷 274-283页

作者： Wang, Yunlong Djuric, Petar M. SUNY Stony Brook Dept Elect & Comp Engn Stony Brook NY 11794 USA

In this paper, we study the problem of distributed hypothesis testing in cooperative networks of agents over a given undirected graph. All the agents try to reach consensus on the state of nature based on their private signals and the binary actions of their neighbors. This is a challenging problem because the exchanged information of the agents regarding their observations used for making decisions is highly compressed. We propose a set of gossip-type methods for which two communicating agents reach the optimal local consensus with probability one by a few exchanges of binary actions at every time slot. We prove that the decision of each agent converges in probability to the optimal decision held by a fictitious fusion center. We also provide theoretical results on how the edge selection probability effects the expected time at which a consensus of all the agents is reached. Simulation results that demonstrate the communication cost and the convergence time of the method are provided.

关键词： Binary consensus distributed detection gossip algorithm multi-agent system

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gossip-Based Load Balance Strategy in Big Data Systems with Hierarchical Processors

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WIRELESS PERSONAL COMMUNICATIONS 2018年第1期98卷 157-172页

作者： Cao, Xiufeng Gao, Shu Chen, Liangchen Wuhan Univ Technol Sch Comp Sci & Technol Wuhan 430000 Hubei Peoples R China China Inst Ind Relat Dept Comp Applicat Beijing 100048 Peoples R China

In big data systems, data are assigned to different processors by the system manager, which has a large amount of work to perform, such as achieving load balances and allocating data to the system processors in a centralized way. To alleviate its load, we claim that load balancing can be conducted in a decentralized way, and thus, the system manager need not be in charge of this task anymore. Two decentralized approaches are proposed for load balancing schemes, namely, a utilization scheme based on a load balance algorithm (UBLB) and a number of layers scheme based on a load balance algorithm (NLBLB). In the UBLB scheme, considering the hierarchy of the processor's processing abilities, a gossip-based algorithm is proposed to achieve load balance using the jobs' utilizations as load balance indicators in addition to the number of jobs. The reason for this action is that the processor's process abilities are different from one another. Thus, the utilization indicator is more reasonable. In the NLBLB scheme, the processors are classified into different layers according to their processing abilities. In each layer, a sub-load balance is conducted, which means that the UBLB is achieved in a sub-region. The efficiencies of the two proposed schemes are validated by simulation, which proves their positive effect.

关键词： Big data system Hierarchical processors Load balance gossip algorithm

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Multiplex Conductance and gossip Based Information Spreading in Multiplex Networks

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2019年第3期6卷 391-401页

作者： Huang, Yufan Dai, Huaiyu North Carolina State Univ Dept Elect & Comp Engn Raleigh NC 27695 USA

In this network era, not only people are connected, different networks are also coupled through various interconnections. This kind of network of networks, or multilayer networks, has attracted research interest recently, and many beneficial features have been discovered. However, quantitative study of information spreading in such networks is essentially lacking. Despite some existing results in single networks, the layer heterogeneity and complicated interconnections among the layers make the study of information spreading in this type of networks challenging. In this work, we study the information spreading time in multiplex networks, adopting the gossip (random-walk) based information spreading model. A new metric called multiplex conductance is defined based on the multiplex network structure and used to quantify the information spreading time in a general multiplex network in the idealized setting. Multiplex conductance is then evaluated for some interesting multiplex networks to facilitate understanding in this new area. Finally, the tradeoff between the information spreading efficiency improvement and the layer cost is examined to explain the user's social behavior and motivate effective multiplex network designs.

关键词： Multiplexing Nonhomogeneous media Measurement Social network services Heuristic algorithms Mathematical model Dynamic scheduling Information spreading multiplex networks gossip algorithm multiplex conductance

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gossip-based distributed stochastic mirror descent for constrained optimization

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NEURAL NETWORKS 2024年 175卷 106291页

作者： Fang, Xianju Zhang, Baoyong Yuan, Deming Nanjing Univ Sci & Technol Sch Automat Nanjing 210094 Jiangsu Peoples R China

This paper considers a distributed constrained optimization problem over a multi -agent network in the nonEuclidean sense. The gossip protocol is adopted to relieve the communication burden, which also adapts to the constantly changing topology of the network. Based on this idea, a gossip -based distributed stochastic mirror descent (GB-DSMD) algorithm is proposed to handle the problem under consideration. The performances of GB-DSMD algorithms with constant and diminishing step sizes are analyzed, respectively. When the step size is constant, the error bound between the optimal function value and the expected function value corresponding to the average iteration output of the algorithm is derived. While for the case of the diminishing step size, it is proved that the output of the algorithm uniformly approaches to the optimal value with probability 1. Finally, as a numerical example, the distributed logistic regression is reported to demonstrate the effectiveness of the GB-DSMD algorithm.

关键词： Stochastic mirror descent Distributed constrained optimization Distributed convex optimization gossip algorithm

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Resilient gossip-inspired all-reduce algorithms for high-performance computing: Potential, limitations, and open questions

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INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2019年第2期33卷 366-383页

作者： Casas, Marc Gansterer, Wilfried N. Wimmer, Elias Barcelona Supercomp Ctr Barcelona Spain Univ Vienna Fac Comp Sci Res Grp Theory & Applicat Algorithms Vienna Austria TU Wien Fac Informat Res Grp Parallel Comp Vienna Austria

We investigate the usefulness of gossip-based reduction algorithms in a high-performance computing (HPC) context. We compare them to state-of-the-art deterministic parallel reduction algorithms in terms of fault tolerance and resilience against silent data corruption (SDC) as well as in terms of performance and scalability. New gossip-based reduction algorithms are proposed, which significantly improve the state-of-the-art in terms of resilience against SDC. Moreover, a new gossip-inspired reduction algorithm is proposed, which promises a much more competitive runtime performance in an HPC context than classical gossip-based algorithms, in particular for low accuracy requirements.

关键词： All-to-all reduction all-reduce gossip algorithm fault tolerance bit-flip silent data corruption recursive doubling push-flow algorithm

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Constraint-Driven Type-2 Fuzzy C-Means Clustering and Step-Wise gossip for Fusion Transmission in Distributed Networks

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IEEE COMMUNICATIONS LETTERS 2024年第5期28卷 1226-1230页

作者： Lu, Yang Zheng, Yan Xiang, Wei Northeast Forestry Univ Coll Comp & Control Engn Harbin 150001 Peoples R China Harbin Normal Univ Dept Comp Sci & Informat Engn Songbei Campus Harbin 150025 Peoples R China La Trobe Univ Sch Comp Engn & Math Sci Melbourne Vic 3086 Australia

The gossip algorithm is an important communication protocol that can be used in various fields, including computer networks and distributed systems. This letter proposes an integrated approach that combines Constraint-Driven Type-2 Fuzzy C-Means (T2FCM) clustering and the step-wise gossip algorithm to overcome the challenges of communication congestion in peer-to-peer distributed networks. Traditional clustering algorithms often lack accuracy and relevance in organizing and analyzing large volumes of data in nodes. To address this, the integration of T2FCM clustering, which incorporates domain-specific constraints, is introduced to improve clustering accuracy. Additionally, the transition state theory based step-wise gossip algorithm is utilized to adjust information transfer rates, enhancing scalability, fault tolerance, and resource utilization while reducing communication congestion. Simulation results demonstrate the effectiveness of the proposed approach in achieving low latency access. By leveraging accurate clustering results and adjusting information transfer rates, the overall performance of fusion transmission in peer-to-peer networks is significantly improved.

关键词： Clustering algorithms Linear programming Peer-to-peer computing Energy states Protocols Fuzzy sets Fault tolerant systems gossip algorithm communication protocol information dissemination type-2 fuzzy C-Means transition state theory

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Asynchronous gossip for Averaging and Spectral Ranking

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IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING 2014年第4期8卷 703-716页

作者： Borkar, Vivek S. Makhijani, Rahul Sundaresan, Rajesh Indian Inst Technol Dept Elect Engn Bombay 400076 Maharashtra India Indian Inst Sci Dept Elect Commun Engn Bangalore 560012 Karnataka India

We consider two variants of the classical gossip algorithm. The first variant is a version of asynchronous stochastic approximation. We highlight a fundamental difficulty associated with the classical asynchronous gossip scheme, viz., that it may not converge to a desired average, and suggest an alternative scheme based on reinforcement learning that has guaranteed convergence to the desired average. We then discuss a potential application to a wireless network setting with simultaneous link activation constraints. The second variant is a gossip algorithm for distributed computation of the Perron-Frobenius eigenvector of a nonnegative matrix. While the first variant draws upon a reinforcement learning algorithm for an average cost controlled Markov decision problem, the second variant draws upon a reinforcement learning algorithm for risk-sensitive control. We then discuss potential applications of the second variant to ranking schemes, reputation networks, and principal component analysis.

关键词： gossip algorithm asynchronous stochastic approximation Poisson equation learning Perron-Frobenius eigenvector ranking

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Distributed DOA Estimation in Wireless Sensor Networks Using Randomized gossip Method

Distributed DOA Estimation in Wireless Sensor Networks Using...

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IEEE International Conference on Ubiquitous Wireless Broadband (ICUWB)

作者： Zhang, Li Xie, Ning Wang, Hui Shenzhen Univ CIE Shenzhen 518060 Guangdong Peoples R China Shenzhen Key Lab Adv Commun & Informat Proc Shenzhen 518060 Peoples R China

ISBN: (纸本)9781467365550

In this paper, we consider the problem of direction of arrival (DOA) estimation achieved by a distributed way in wireless sensors networks. The goal for each node is to detect targets based on its local information and that of its neighbors through some iteration. Classic estimation methods, such as maximum likelihood (ML) algorithm, are not suitable here because there is often a requirement of a central unit to obtain the optimal solution. We propose a new distributed DOA estimation algorithms based on the randomized gossip method, the goal of which is to realize the conventional Capon method by a distributed way. The proposed algorithm does not require any constraint on the network geometries, thereby making it suitable for distributed signal processing in large wireless sensor networks. The given simulation results illustrate the main characteristics of the proposed algorithm, including DOA resolution and mean square error (MSE) performance.

关键词： Distributed DOA estimation Wireless sensors networks gossip algorithm

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Convergence Acceleration of gossip Protocols Applied for Decentralized Distribution Grid Management

Convergence Acceleration of Gossip Protocols Applied for Dec...

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PowerTech, 2015 IEEE Eindhoven

作者： Koukoula, Despina I. Hatziargyriou, Nikos D. Natl Tech Univ Athens Dept Elect Engn Athens Greece

ISBN: (纸本)9781479976959

The paper describes a gossip protocol based architecture for detecting and resolving overvoltage or undervoltage problems of distribution lines applying Distributed Energy Resources (DERs) management in a decentralized manner. The proposed algorithm is based on the application of gossip protocols to estimate locally critical physical quantities. The paper focuses on the optimal selection of the weights in order to accelerate the convergence of the gossip algorithm.

关键词： Distributed algorithms gossip algorithm Smart grid Distribution grid management

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