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IMPROVED ALGORITHM FOR decentralized EXTREMA-FINDING IN CIRCULAR CONFIGURATIONS OF PROCESSES

COMMUNICATIONS OF THE ACM 1979年第5期22卷 281-283页

作者： CHANG, E ROBERTS, R UNIV TORONTO TORONTO M5S 1A1ONTARIOCANADA

This note presents an improvement to LeLann's algorithm for finding the largest (or smallest) of a set of uniquely numbered processes arranged in a circle, in which no central controller exists and the number of processes is not known a priori. This decentralized algorithm uses a technique of selective message extinction in order to achieve an average number of message passes of order (n log n) rather than O(n2).

关键词： decentralized algorithms distributed systems operating systems

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An Approximate Min-Sum Algorithm for Smart Grid Dispatch with Continuous Variables

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IFAC-PapersOnLine 2016年第27期49卷 307-312页

作者： Kellerer, Anna Elisabeth Steinke, Florian Technical University Munich Munich Germany Siemens Corporate Technology Munich Germany

We present a decentralized algorithm for solving economic dispatch problems in tree-shaped electrical distribution grids. Previous work used an extension of dynamic programming to trees, i.e. the min-sum algorithm, with discrete variables to solve these problems. We now present a novel, specially adapted, and efficient approximation scheme for continuous variables. Working with continuous variables is mandatory for many real world applications where line, consumption and generator capacities often have significantly different scales. © 2016

关键词： Electric load dispatching Dynamic programming Electric power transmission networks Forestry Scheduling Smart power grids Trees (mathematics) Approximation scheme Continuous variables decentralized algorithms Distribution grid Economic Dispatch Economic dispatch problems Electrical distribution Smart grid

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Backhaul-Constrained Multicell Cooperation Leveraging Sparsity and Spectral Clustering

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2016年第2期15卷 899-912页

作者： Jain, Swayambhoo Kim, Seung-Jun Giannakis, Georgios B. Univ Minnesota Dept Elect & Comp Engn Minneapolis MN 55455 USA Univ Maryland Dept Comp Sci & Elect Engn Baltimore MD 21250 USA

Multicell cooperative processing with limited backhaul traffic is studied for cellular uplinks. Aiming at reduced backhaul overhead, a sparse multicell linear receive-filter design problem is formulated. Both unstructured distributed cooperation and clustered cooperation, in which base station groups are formed for tight cooperation, are considered. Dynamic clustered cooperation, where the sparse equalizer and the cooperation clusters are jointly determined, is solved via alternating minimization based on spectral clustering and group-sparse regression. Furthermore, decentralized implementations of both unstructured and clustered cooperation schemes are developed for scalability, robustness, and computational efficiency. Extensive numerical tests verify the efficacy of the proposed methods.

关键词： Coordinated multi-point decentralized algorithms multicell cooperation sparsity

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Work Capacity of Regulated Freelance Platforms: Fundamental Limits and decentralized Schemes

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IEEE-ACM TRANSACTIONS ON NETWORKING 2017年第6期25卷 3641-3654页

作者： Chatterjee, Avhishek Varshney, Lav R. Vishwanath, Sriram IIT Madras Dept Elect Engn Madras 600036 Tamil Nadu India Univ Illinois Coordinated Sci Lab Urbana IL 61801 USA Univ Texas Austin Dept Elect & Comp Engn Austin TX 78712 USA

Crowdsourcing of jobs to online freelance platforms is rapidly gaining popularity. Most crowdsourcing platforms are uncontrolled and offer freedom to customers and freelancers to choose each other. This works well for unskilled jobs (e.g., image classification) with no specific quality requirement since freelancers are functionally identical. For skilled jobs (e.g., software development) with specific quality requirements, however, this does not ensure that the maximum number of job requests is satisfied. In this paper, we determine the capacity of regulated freelance systems, in terms of maximum satisfied job requests, and propose centralized schemes that achieve capacity. To ensure decentralized operation and freedom for customers and freelancers, we propose simple schemes compatible with the operation of current crowdsourcing platforms that approximately achieve capacity. Furthermore, for settings where the number of job requests exceeds capacity, we propose a scheme that is agnostic of that information, but is optimal and fair in declining jobs without wait.

关键词： Freelance platforms capacity queuing decentralized algorithms

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A decentralized VARIANCE-REDUCED METHOD FOR STOCHASTIC OPTIMIZATION OVER DIRECTED GRAPHS

A DECENTRALIZED VARIANCE-REDUCED METHOD FOR STOCHASTIC OPTIM...

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IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Qureshi, Muhammad, I Xin, Ran Kar, Soummya Khan, Usman A. Tufts Univ Medford MA 02155 USA Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9781728176055

In this paper, we propose a decentralized first-order stochastic optimization method Push-SAGA for finite-sum minimization over a strongly connected directed graph. This method features local variance reduction to remove the uncertainty caused by random sampling of the local gradients, global gradient tracking to address the distributed nature of the data, and push-sum consensus to handle the imbalance caused by the directed nature of the underlying graph. We show that, for a sufficiently small step-size, Push-SAGA linearly converges to the optimal solution for smooth and strongly convex problems, making it the first linearly-convergent stochastic algorithm over arbitrary strongly-connected directed graphs. We illustrate the behavior and convergence properties of Push-SAGA with the help of numerical experiments for strongly convex and non-convex problems.

关键词： Stochastic optimization first-order methods variance reduction decentralized algorithms directed graphs

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decentralized spectrum and radio resource management enabled by an on-demand Cognitive Pilot Channel 13

Decentralized spectrum and radio resource management enabled...

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13th European Wireless Conference

作者： Sallent, O. Agusti, R. Perez-Romero, J. Giupponi, L. Univ Politecn Cataluna Dept Signal Theory & Commun ES-08034 Barcelona Spain

This paper presents a framework to achieve an efficient dynamic and decentralized spectrum and radio resource usage in heterogeneous wireless network scenarios. The envisaged technical solution follows a layered approach, where joint radio resource management (JRRM) and advanced spectrum management mechanisms are identified at both the intra- and inter-operator levels. The importance of cognitive network functionalities is highlighted. An on-demand Cognitive Pilot Channel (CPC) is proposed as radio enabler solution for decentralized operation with decision making processes executed at the mobile terminal side. The suitability of the proposed solution is shown by comparison with a broadcast CPC approach. Finally, the paper presents and evaluates decentralized JRRM algorithms both at the intra- and inter-operator levels using the proposed framework.

关键词： advanced spectrum management joint radio resource management decentralized algorithms Cognitive Pilot Channel cognitive networks

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Pricing and Power allocation in Femtocells using Stackelberg Game Theory 10

Pricing and Power allocation in Femtocells using Stackelberg...

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International Conference on Signal Processing and Communications (SPCOM)

作者： Sankar, V. Udaya Sharma, Vinod Indian Inst Sci Dept Elect Commun Engn Bangalore 560012 Karnataka India

ISBN: (纸本)9781479946655

We consider a system with multiple Femtocells operating in a Macrocell. The transmissions in one Femtocell interfere with its neighboring Femtocells as well as with the Macrocell Base Station. We model Femtocells as selfish nodes and the Macrocell Base Station protects itself by pricing subchannels for each usage. We use Stackelberg game model to study this scenario and obtain equilibrium policies that satisfy certain quality of service.

关键词： Femtocell cellular communication power control QoS Game theory decentralized algorithms Stackelberg Game

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Introducing decentralized EV Charging Coordination for the Voltage Regulation

Introducing Decentralized EV Charging Coordination for the V...

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4th IEEE/PES Innovative Smart Grid Technologies Europe (ISGT EUROPE)

作者： Beaude, Olivier He, Yujun Hennebel, Martin Supelec Power Syst Dept L2S Paris France Renault SAS Paris France Supelec Power Syst Dept Paris France Supelec Power Syst Dept E3S Gif Sur Yvette France

ISBN: (纸本)9781479929849

This paper investigates a decentralized optimization methodology to coordinate Electric Vehicles (EV) charging in order to contribute to the voltage control on a residential electrical distribution feeder. This aims to maintain the voltage level in function of the EV's power injection using the sensitivity matrix approach. The decentralized optimization is tested with two different methods, respectively global and local, when EV take into account their impact on all the nodes of the network or only on a local neighborhood of their connection point. EV can also update their decisions asynchronously or synchronously. While only the global approach with asynchronous update is theoretically proven to converge, using results from game theory, simulations show the potential of other algorithms for which fewer iterations or fewer informations are necessary. Finally, using Monte Carlo simulations over a wide range of EV localization configurations, the first analysis have also shown a promising performance in comparison with uncoordinated charging or with a "voltage droop charging control" recently proposed in the literature.

关键词： Voltage control decentralized algorithms EV charging Game theory

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Joint scheduling and resource allocation for multiple video decoding tasks

Joint scheduling and resource allocation for multiple video ...

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15th Conference on Multimedia Computing and Networking 2008

作者： Foo, Brian van der Schaar, Mihaela Univ Calif Los Angeles Dept Elect Engn EE Los Angeles CA 90095 USA

ISBN: (纸本)9780819469908

In this paper we propose a joint resource allocation and scheduling algorithm for video decoding on a resource-constrained system. By decomposing a multimedia task into decoding jobs using quality-driven priority classes, we demonstrate using queuing theoretic analysis that significant power savings can be achieved under small video quality degradation without requiring the encoder to adapt its transmitted bitstream. Based on this scheduling algorithm, we propose an algorithm for maximizing the sum of video qualities in a multiple task environment, while minimizing system energy consumption, without requiring tasks to reveal information about their performances to the system or to other potentially exploitative applications. Importantly, we offer a method to optimize the performance of multiple video decoding tasks on an energy-constrained system, while protecting private information about the system and the applications.

关键词： information privacy priority scheduling queuing theory decentralized algorithms complexity-scalable multimedia applications

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A PROJECTION-FREE decentralized ALGORITHM FOR NON-CONVEX OPTIMIZATION

A PROJECTION-FREE DECENTRALIZED ALGORITHM FOR NON-CONVEX OPT...

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IEEE Global Conference on Signal and Information Processing (GlobalSIP)

作者： Wai, Hoi-To Scaglione, Anna Lafond, Jean Moulines, Eric Arizona State Univ Sch ECEE Tempe AZ 85287 USA Ecole Polytech CMAP Palaiseau France CNRS LTCI Telecom ParisTech Inst Mines Telecom Paris France

ISBN: (纸本)9781509045457

This paper considers a decentralized projection free algorithm for non-convex optimization in high dimension. More specifically, we propose a decentralized Frank-Wolfe (DeFW) algorithm which is suitable when high dimensional optimization constraints are difficult to handle by conventional projection/proximal-based gradient descent methods. We present conditions under which the DeFW algorithm converges to a stationary point and prove that the rate of convergence is as fast as O(1/root T), where T is the iteration number. This paper provides the first convergence guarantee for Frank-Wolfe methods applied to non-convex decentralized optimization. Utilizing our theoretical findings, we formulate a novel robust matrix completion problem and apply DeFW to give an efficient decentralized solution. Numerical experiments are performed on realistic and synthetic data to support our findings.

关键词： non-convex optimization Frank-Wolfe method decentralized algorithms gossip algorithms matrix completion

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