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检索条件"主题词=distributed algorithms"

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Enhancing Two Phase-Commit Protocol for Replicated State Machines

Enhancing Two Phase-Commit Protocol for Replicated State Mac...

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Euromicro Conference on Parallel, distributed and Network-Based Processing

作者： Halit Uyanık Tolga Ovatman Department of Computer Engineering Istanbul Technical University Istanbul Turkey

ISBN: (数字)9781728165820

ISBN: (纸本)9781728165837

Two-Phase commit (2PC) is a distributed algorithm where a process which wishes to make a commit on a service first needs to make sure that the participating peers are ready for the commit operation. In our study we enhance 2PC for replicated state machine environments by early aborting the state executions of a state machine in case a higher priority state machine checks to commit a value to be written. By applying our approach, when the number of replicas goes beyond 3 our approach wastes significantly less state executions compared to classical 2PC.

关键词： Protocols distributed algorithms distributed computing

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Detection of Near Duplicates over Graph Datasets Using Pruning

Detection of Near Duplicates over Graph Datasets Using Pruni...

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India Council International Subsections Conference (INDISCON), IEEE

作者： Prathi Naveena P.Krishna Subba Rao Gayatri Vidya Parishad College of Engineering (A) Visakhapatnam India

ISBN: (数字)9781728187341

ISBN: (纸本)9781728187358

Graphs are widely used formalism to model data in various domains such as natural language processing, chemoinformatics, computer vision, information retrieval and software engineering. Finding similar graphs is essential for many applications in these domains. Graph isomorphism finds exact duplicate graphs. However, it fails to quantify similarity and it's computationally expensive. To overcome both these bottlenecks, a number of graph similarity measures have been proposed. Graph Similarity Self-Join (GSSJ) is the problem of finding all pairs of graphs that have similarity score above a predefined threshold. For a graph dataset with n graphs, Naive solution involves similarity score computation for all (n/2) pairs of graphs. This problem is both compute and data intensive. Existing algorithms for this problem support only graph edit distance as the similarity measure. Overarching goal of this research is to develop algorithms for graph similarity self-join that support multiple graph similarity measures. Major contribution of this research will be better indexing mechanisms for graphs and tight bounds on graph similarity.

关键词： Filtering Information retrieval Natural language processing Data models distributed algorithms Software engineering Indexing

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Matching Affinity Clustering: Improved Hierarchical Clustering at Scale with Guarantees 20

Matching Affinity Clustering: Improved Hierarchical Clusteri...

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Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems

作者： MohammadTaghi Hajiaghayi Marina Knittel University of Maryland College Park College Park MD USA

ISBN: (纸本)9781450375184

Hierarchical clustering is a stronger extension of one of today's most influential unsupervised learning methods: clustering. The goal of this method is to create a hierarchy of clusters, thus constructing cluster evolutionary history and simultaneously finding clusterings at all resolutions. We propose four traits of interest for hierarchical clustering algorithms: (1) empirical performance, (2) theoretical guarantees, (3) balance (the minimum ratio between cluster sizes), and (4) scalability. While a number of algorithms are designed to achieve one to two of these traits at a time, there exist none that achieve all *** by Bateni et al.'s scalable and empirically successful Affinity Clustering [NeurIPs 2017], we introduce Affinity's successor, Matching Affinity Clustering. Like its predecessor, Matching Affinity Clustering maintains strong empirical performance, even outperforming Affinity when the dataset is size 2n and clusters are balanced, and uses Massively Parallel Communication as its distributed model. Designed to maintain provably balanced clusters, we show that our algorithm achieves a (1/3-ε)-approximation for Moseley and Wang's revenue (the dual to Dasgupta's cost) when the data set is of size 2n, and a (1/9-ε)-approximation in general. We prove the former approximation is tight, and also that Affinity Clustering cannot do better than a 1/O(n)-approximation. In addition, we see that our algorithm empirically performs similarly to Affinity Clustering and k-Means, outperforming many state-of-the-art serial algorithms. Along the way, we also introduce an efficient k-sized maximum matching algorithm in the MPC model.

关键词： massively parallel communication graph algorithms distributed algorithms hierarchical clustering maximum matching approximation algorithms unsupervised learning mapreduce

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Efficient Process-to-Node Mapping algorithms for Stencil Computations

Efficient Process-to-Node Mapping Algorithms for Stencil Com...

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IEEE International Conference on Cluster Computing

作者： Konrad von Kirchbach Markus Lehr Sascha Hunold Christian Schulz Jesper Larsson Träff TU Wien Faculty of Informatics Vienna Austria University of Vienna Faculty of Computer Science Vienna Austria

ISBN: (数字)9781728166773

ISBN: (纸本)9781728166780

Good process-to-compute-node mappings can be decisive for well performing HPC applications. A special, important class of process-to-node mapping problems is the problem of mapping processes that communicate in a sparse stencil pattern to Cartesian grids. By thoroughly exploiting the inherently present structure in this type of problem, we devise three novel distributed algorithms that are able to handle arbitrary stencil communication patterns effectively. We analyze the expected performance of our algorithms based on an abstract model of inter- and intra-node communication. An extensive experimental evaluation on several HPC machines shows that our algorithms are up to two orders of magnitude faster in running time than a (sequential) high-quality general graph mapping tool, while obtaining similar results in communication performance. Furthermore, our algorithms also achieve significantly better mapping quality compared to previous state-of-the-art Cartesian grid mapping algorithms. This results in up to a threefold performance improvement of an MPI_Neighbor_alltoall exchange operation. Our new algorithms can be used to implement the MPI_Cart_create functionality.

关键词： Conferences Clustering algorithms Cluster computing Tools Benchmark testing Computational efficiency distributed algorithms

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Network-Constrained Controllable Load Management: A Game Theoretic Approach

Network-Constrained Controllable Load Management: A Game The...

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IEEE International Conference on Power and Power and Renewable Energy (ICPRE)

作者： Yifei Wang Xiuli Wang Qiao Peng School of Electrical Engineering Xi’an Jiaotong University Xi’an China

ISBN: (数字)9781728190266

ISBN: (纸本)9781728190273

Controllable load management can effectively encourage consumers to control consumption and reduce bills. This paper considers a smart distribution system where consumers are managed by load aggregators (LAs). In the framework of dynamic pricing, the LAs must compete to obtain the satisfied consumption. However, this behavior may violate the network constraints of the distribution system. Therefore, a network-constrained energy consumption (NCEC) game model among active load aggregators (ALAs) is proposed to guarantee the safety of the distribution system. Then the generalized Nash equilibrium (GNE) for the model is proved to be exist. Furthermore, a distributed algorithm based on proximal decomposition is proposed to find one of the GNEs. Finally, the effectiveness of the proposed game model and the efficiency of the distributed algorithm are tested on an IEEE-33 bus system.

关键词： controllable load management safety of the distribution system generalized Nash equilibrium proximal decomposition dispensing system Nash equilibrium load management distributed algorithms Hunting Game theory Game animals Consumers lanthanum

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Solving Least Squares for Linear Equations over Strongly Connected Directed Networks

Solving Least Squares for Linear Equations over Strongly Con...

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Control Conference (ANZCC), Australian and New Zealand

作者： Mohammad Jahvani Martin Guay Queen's University Kingston ON Canada

ISBN: (数字)9781728199924

ISBN: (纸本)9781728199931

In this paper, we introduce a distributed continuous-time flow on directed networks for the computation of least-squares solution to a linear algebraic equation of the form Ax=b where A has full column rank. It is assumed that each one of the n autonomous agents only knows a subset of the partitioned matrix [A b]. Each agent in the network is able to send information to certain other agents called its “out-neighbors”. Neighbor relations are characterized by a directed graph G whose vertices correspond to the labels of agents and whose edges depict the neighbor relations. It is shown that for any such matrix A and any strongly connected neighbor graph, the estimates of all agents in the proposed algorithm converge exponentially to the desired solution (A ' A) -1 A ' b, even if only one of the agents across the network uses a nonzero and sufficiently small constant step-size.

关键词： Mathematical model Heuristic algorithms distributed algorithms Convergence Matrix decomposition Iterative methods Safety

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Decentralized Exploration of a Structured Environment Based on Multi-agent Deep Reinforcement Learning

Decentralized Exploration of a Structured Environment Based ...

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International Conference on Parallel and distributed Systems (ICPADS)

作者： Dingjie He Dawei Feng Hongda Jia Hui Liu College of Computer National University of Defense Technology Changsha China

ISBN: (数字)9781728190747

ISBN: (纸本)9781728183824

Multi-robot environment exploration is one of the widely discussed topics in the field of robotics. It is the foundation for many real-world robotic applications. Many decentralized methods (that is, without a centralized controller) have been proposed in the past decades. Most of them focus on improving collaboration efficiency by utilizing low-level heuristic information, such as distances to obstacles and robot positions. In contrast, although a human being can make decisions on a similar task, he/she exploits high-level knowledge, such as the building's common structure pattern. This paper proposes a novel distributed multi-robot exploration algorithm based on deep reinforcement learning (DME-DRL) for structured environments that enables robots to make decisions on the basis of this high-level knowledge. DME-DRL is a distributed algorithm that uses deep neural networks to extract the structural pattern of the environment, and it can work in scenarios with or without communication. The experimental results showed that this approach can decrease the travel distance by approximately 10.84% on average, compared with those of traditional heuristic methods and can significantly reduce the communication cost in the exploration process.

关键词： Conferences Neural networks Collaboration Reinforcement learning Task analysis distributed algorithms Robots

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An Asynchronous Game-based algorithm to the Weighted Vertex Cover of Networks

An Asynchronous Game-based algorithm to the Weighted Vertex ...

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Computer Engineering and Intelligent Control (ICCEIC) International Conference on

作者： Kaiyi Luo College of Mathematics and Computer Sciences Zhejiang Normal University Jinhua China

ISBN: (数字)9781728185736

ISBN: (纸本)9781728185743

Minimum weighted vertex cover (MWVC) problem of weighted networks is one of the most important combinatorial optimization problems in network optimization. This paper models the MWVC problem as an asymmetric game on weighted networks. Then, an asynchronous game-based algorithm (AGB) is proposed to solve the MWVC problem, which can guarantee to obtain a vertex cover (VC). Numerical illustrations verify the performance of the proposed game solution on the representative weighted networks.

关键词： Computational modeling Games Numerical simulation Numerical models distributed algorithms Optimization Intelligent control

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Study on Stocks Based on Big Data Methods and Computer Programs

Study on Stocks Based on Big Data Methods and Computer Progr...

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Image Processing, Electronics and Computers (IPEC), Asia-Pacific Conference on

作者： Cheng Wang Hailei Zou Juncheng Yin Applied Math Dept China Jiliang Univ. Hang Zhou City China

ISBN: (数字)9781728160672

ISBN: (纸本)9781728160689

Recently big data is a hot topic in many fields. Here we use distributed algorithms to treat big data in Chinese stock market. First the two stock indexes (Shanghai Composite and Shenzhen Composite indexes) from 1990-2019 are collected. Then the data are divided to several subsets and are analyzed separately via computer programs. Finally the results for every subset are combined due to distributed algorithms theory. In addition to big data scheme, we adopt stochastic processes theory and moment equations methods.

关键词： distributed algorithm Big data Lèvy processes Chinese stock index Moment estimations Lè vy processes big data distributed algorithms stocks Computers

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Using Model Checking to Formally Verify Rendezvous algorithms for Robots with Lights in Euclidean Space

Using Model Checking to Formally Verify Rendezvous Algorithm...

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Reliable distributed Systems

作者： Xavier Défago Adam Heriban Sébastien Tixeuil Koichi Wada School of Computing Tokyo Institute of Technology Tokyo Japan CNRS LIP6 Sorbonne Université Paris France Faculty of Science & Engineering Hosei University Tokyo Japan

ISBN: (数字)9781728176260

ISBN: (纸本)9781728176277

The paper details the first successful attempt at using model checking techniques to verify the correctness of distributed algorithms for robots evolving in a continuous environment. The study focuses on the problem of rendezvous of two robots with *** exist many different rendezvous algorithms that aim at finding the minimal number of colors needed to solve rendezvous in various synchrony models (e.g., FSYNC, SSYNC, ASYNC). While these rendezvous algorithms are typically very simple, their analysis and proof of correctness tend to be extremely complex, tedious, and error-prone as impossibility results are based on subtle interactions between robots activation *** paper presents a generic verification model written for the SPIN model checker. In particular, we explain the subtle design decisions that allow to keep the search space finite and tractable, as well as prove several important theorems that support them. As a sanity check, we use the model to verify several known rendezvous algorithms in six different models of synchrony. In each case, we find that the results obtained from the model checker are consistent with the results known in the literature. The model checker outputs a counter-example execution in every case that is known to *** the course of developing and proving the validity of the model, we identified several fundamental theorems, including the ability for a well chosen algorithm and ASYNC scheduler to produce an emerging property of memory in a system of oblivious mobile robots, and why it is not a problem for luminous rendezvous algorithms.

关键词： Analytical models Color Model checking Reliability Mobile robots distributed algorithms

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