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decentralized algorithm for Centralized Variational Inequalities in Network Resource Allocation

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 2011年第3期151卷 525-540页

作者： Iiduka, Hideaki Kyushu Inst Technol Network Design Res Ctr Chiyoda Ku Tokyo 1000011 Japan

decentralized algorithms would be useful for making network resource allocations in large-scale and complex system networks because such networks tend to lack centralized operators and are subject to continuous infrastructure improvements. In this paper, we consider a variational inequality for network resource allocation and devise a decentralized allocation algorithm for it. The proposed algorithm enables each user in the network to decide its own optimal resource allocation in cooperation with other users without using other users' private information such as their utility functions. Moreover, we present a convergence analysis on the algorithm and apply it to the network resource allocation problem.

关键词： Monotone operator Resolvent Centralized optimization problem Variational inequality Network resource allocation problem decentralized algorithm

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decentralized algorithm applicable to parallel trajectory planning of multiple aircraft

Decentralized algorithm applicable to parallel trajectory pl...

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International Conference on Control, Automation and Systems

作者： Yokoyama, Nobuhiro Natl Def Acad Dept Aerosp Engn Yokosuka Kanagawa 239 Japan

ISBN: (纸本)9788995003879

Conventional algorithms for autonomous trajectory planning of multiple aircraft tend to require prohibitive computational time as the number of concerned aircraft increases. To overcome this drawback, this paper presents a fast and decentralized trajectory planning algorithm which can be executed in parallel. The developed algorithm combines force field method for conflict reduction and quadratic programming for trajectory optimization. Due to the parallel nature, the computational time in the developed algorithm is not as sensitive to the number of concerned aircraft as the conventional algorithms. Several results of numerical simulations are presented to demonstrate the performance of the developed algorithm.

关键词： trajectory optimization quadratic programming decentralized algorithm

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EdgeDecAp: An auction-based decentralized algorithm for optimizing application placement in edge computing

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JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 2023年 175卷 22-36页

作者： Smolka, Sven Wissenberg, Leon Mann, Zoltan Adam Univ Duisburg Essen Essen Germany Univ Amsterdam Amsterdam Netherlands

In edge computing, application components can be placed over a range of computational devices from cloud data centers to nodes at the network edge. Application placement can have significant impact on important metrics like latency and resource utilization. Thus, application placement is an important optimization problem. In edge computing, the characteristics of both the infrastructure and the application may change over time, which may require the dynamic re-optimization of the application placement. Most algorithms suggested so far for the dynamic re-optimization of edge application placement are centralized, i.e., they rely on one entity collecting information from the whole infrastructure and making decisions centrally. However, centralized approaches suffer from limited scalability and are vulnerable to *** this paper, we present a decentralized approach for the dynamic re-optimization of edge application placement. We adopt an algorithm of Malek et al. for distributed systems and modify it to make it applicable to edge computing. In this approach, each node makes decisions autonomously, using auctions for coordination. Our empirical results demonstrate that the proposed algorithm is very effective in optimizing edge application placement. In an edge system with 637 edge nodes and 563 end devices, our algorithm achieves 54% higher reduction of application latency than a previous decentralized algorithm.(c) 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons .org /licenses /by-nc -nd /4 .0/).

关键词： Edge computing Fog computing Application placement decentralized algorithm Auction

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A decentralized algorithm for spectral analysis

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JOURNAL OF COMPUTER AND SYSTEM SCIENCES 2008年第1期74卷 70-83页

作者： Kempe, David McSherry, Frank Univ So Calif Dept Comp Sci Los Angeles CA 90089 USA

In many large network settings, such as computer networks, social networks, or hyperlinked text documents, much information can be obtained from the network's spectral properties. However. traditional centralized approaches for computing eigenvectors struggle with at least two obstacles: the data may be difficult to obtain (both due to technical reasons and because of privacy concerns), and the sheer size of the networks makes the computation expensive. A decentralized, distributed algorithm addresses both of these obstacles: it utilizes the computational power of all nodes in the network and their ability to communicate, thus speeding up the computation with the network size. And as each node knows its incident edges, the data collection problem is avoided as well, Our main result is a simple decentralized algorithm for computing the top k eigenvectors, of a symmetric weighted adjacency matrix. and a proof that it converges essentially in O(tau(mix), log(2) n) rounds of communication and computation, where tau(mix), is the mixing time of a random walk on the network. An additional contribution of our work is a decentralized way of actually detecting convergence, and diagnosing the current error. Our protocol scales well, in that the amount of computation performed at any node in any one round, and the sizes of messages sent, depend linearly on the degree of the node, polynomially on k, but not at all on the (typically much larger) number n of nodes. To achieve independence of n, the coordinates of the computed eigenvectors are held locally by the nodes to which they correspond, enabling many eigenanalyses without distributing complete global state. (c) 2007 Elsevier Inc. All rights reserved.

关键词： eigenvectors spectral analysis decentralized algorithm Markov Chain large networks

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DACYCLEM: A decentralized algorithm for maximizing coverage and lifetime in a mobile wireless sensor network

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AD HOC NETWORKS 2019年 87卷 174-187页

作者： Etancelin, Jean-Matthieu Fabbri, Andre Guinand, Frederic Rosalie, Martin Univ Pau & Pays Adour LMAP IPRA UMR5142 F-64013 Pau Pyrenees Atlant France Univ Lyon 1 Univ Lyon CNRS LIRISUMR5205 F-69622 Villeurbanne France Normandie Univ UNIHAVRE LITIS Lab Le Havre France Cardinal Stefan Wyszynski Univ Warsaw Warsaw Poland Univ Luxembourg SnT Luxembourg Luxembourg Univ Perpignan Via Domitia Lab Genome & Dev Plantes UMR5096 F-66860 Perpignan France CNRS Lab Genome & Dev Plantes UMR5096 F-66860 Perpignan France

The goal of Mobile Wireless Sensor Networks (M-WSN) is to sense a specific environment. A commonly considered objective is to organize the work of the sensors such that they monitor the environment as long as possible and cover a surface as large as possible. While most of the time this problem is formulated as a multi-objective optimization problem we present a new decentralized approach for building a connected dominating set (CDS) coupled with attractive and repulsive forces for the movement of sensors in order to maintain the network connectivity. The approach is implemented as a hybrid decentralized algorithm: DACYCLEM (decentralized algorithm under Connectivity constraint with mobilitY for Coverage and LifEtime Maximization). The lifetime and the coverage achieved by our approach are the results of the local interactions between the sensors and were not obtained by the application of a direct optimization method. We also introduce a new metric, the speed of coverage, to evaluate the balance between coverage and lifetime. Finally, our simulation results show that one single parameter of DACYCLEM is responsible for the balancing between coverage and lifetime. (C) 2018 Elsevier B.V. All rights reserved.

关键词： WSN Coverage Connectivity maintenance decentralized algorithm Lifetime maximization

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A Temporal decentralized algorithm for Optimal Stochastic Energy Scheduling in Microgrids

A Temporal Decentralized Algorithm for Optimal Stochastic En...

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IEEE-Power-and-Energy-Society General Meeting (PESGM)

作者： Ju, Chengquan Tang, Yi Wang, Yu Xu, Yan Nanyang Technol Univ Energy Res Inst Singapore Singapore Nanyang Technol Univ Sch Elect & Elect Engn Singapore Singapore

ISBN: (纸本)9781728119816

This paper proposes a decentralized alternating direction method of multipliers (ADMM) algorithm for solving the optimization problem of energy scheduling in microgrids. Different from the other ADMM-based distributed approaches which decomposes the monolithic problem spatially into smaller tractable subproblems, the proposed method adopts a temporal decomposition on the scenario tree inherited from multi-stage stochastic programming. Each node in the scenario tree serves its own optimization with local variables and constraints, and iteratively updates information with adjacent nodes. By implementing the proposed ADMM algorithm in a rolling fashion, simulation results have shown the fast convergence of the temporal distribution framework, and comparisons on optimal value and computation time with other optimization approaches reveals its advantages and effectiveness.

关键词： Microgrids stochastic optimization decentralized algorithm

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A New decentralized algorithm for Optimal Load Shifting via Electric Vehicles 36

A New Decentralized Algorithm for Optimal Load Shifting via ...

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第36届中国控制会议

作者： Hao Xing Zhiyun Lin Minyue Fu School of Automation Hangzhou Dianzi University School of Electrical Engineering and Computer Science University of Newcastle

ISBN: (纸本)9781538629185

In this paper we investigate the optimal load shifting problem via electric vehicles(EVs) in a smart grid scenario which aims at flattening the total demand curve as much as possible while each EV's local constraints are *** assume bidirectional energy exchange between EVs and the power grid and formulate the problem as a mixed integer quadratic programming *** solve this problem in a decentralized fashion,we propose a decentralized optimal algorithm where EVs and the aggregator cooperatively find the optimal solution by communicating in a star network and conducting local *** implement the proposed algorithm,only limited data are exchanged and the aggregator does not need any parameter information of *** proposed algorithm converges much faster than traditional centralized methods/commercial solvers,as the mixed integer part is broken down into local subproblems and solved in parallel by each *** proof of the proposed algorithm is presented and numerical experiments show the effectiveness of the proposed algorithm.

关键词： decentralized algorithm Electric Vehicle Load Shifting Mixed Integer Programming Smart Grid V2G

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A Multi-Agent Based decentralized algorithm for Social Network Community Mining

A Multi-Agent Based Decentralized Algorithm for Social Netwo...

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International Conference on Advances in Social Networks Analysis and Mining

作者： Yang, Bo Huang, Jing Liu, Dayou Liu, Jiming Jilin Univ Coll Comp Sci & Technol Changchun 130023 Peoples R China Hong Kong Baptist Univ Dept Comp Sci Kowloon Peoples R China

ISBN: (纸本)9781424445998

Research has shown that many social networks come into being hierarchically based on some basic building blocks called communities, within which the social interactions are very intensive, but between which they are very weak. Network community mining algorithms aim at efficiently and effectively discovering all such communities from a given network. Many related methods have been proposed and applied to different areas including social network analysis, gene network analysis and web clustering engine. Most of the existing methods for mining communities are centralized. In this paper, we present a multi-agent based decentralized algorithm, in which a group of autonomous agents work together to mine a network through a proposed self-aggregation and self-organization mechanism. Thanks to its decentralized feature, our method is potentially suitable for dealing with distributed networks, whose global structures are hard to obtain due to their geographical distributions, decentralized controls or huge sizes. The effectiveness of our method has been tested against different benchmark networks.

关键词： social network community mining multi-agent system decentralized algorithm

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A decentralized algorithm for spectral analysis

A decentralized algorithm for spectral analysis

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36th Annual ACM Symposium on Theory of Computing

作者： Kempe, David McSherry, Frank Univ So Calif Dept Comp Sci Los Angeles CA 90089 USA

关键词： eigenvectors spectral analysis decentralized algorithm Markov Chain large networks

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On-board Implementation of a decentralized algorithm for Deployment of a Swarm

On-board Implementation of a Decentralized Algorithm for Dep...

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13th International Conference on Computer Aided Systems Theory (EUROCAST)

作者： Passenbrunner, Thomas E. del Re, Luigi Johannes Kepler Univ Linz Inst Design & Control Mechatron Syst A-4040 Linz Austria

ISBN: (纸本)9783642275784

The area of operation of UAS (Unmanned Aircraft Systems) has increased substantially due to falling prizes and increased on-board computational power. Many of these applications are intended to increase the safety of the civil population or to support disaster operations. One of these applications is the measurement of the concentation of toxic gases after an incident in a chemical plant to estimate the release rate. The optimal distribution of the agents of the swarm equipped with pollution sensors in the area to be scanned is an important challenge. The communication between the individual agents as well as with the ground station is limited. Furthermore, a simple function allows a weighting of a distinguished part of the area to be scanned. This paper presents technical basics and a simple, decentralized but yet effective on-board implementation as well as results in simulation.

关键词： UAS (Unmanned Aircraft Systems) Swarm decentralized algorithm Deployment Geometric optimization Partitioning Geometric center Center of gravity

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