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IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Pierluigi Crescenzi Pierre Fraigniaud Ami Paz IRIF CNRS Université de Paris Paris France Faculty of Computer Science University of Vienna Vienna Austria

ISBN: (数字)9781728164120

ISBN: (纸本)9781728164137

Betweenness centrality is a graph parameter that has been successfully applied to network analysis. In the context of computer networks, it was considered for various objectives, ranging from routing to service placement. However, as observed by Maccari et al. [INFOCOM 2018], research on betweenness centrality for improving protocols was hampered by the lack of a usable, fully distributed algorithm for computing this parameter. We resolve this issue by designing an efficient algorithm for computing betweenness centrality, which can be implemented by minimal modifications to any distance-vector routing protocol based on Bellman-Ford. The convergence time of our implementation is shown to be proportional to the diameter of the network.

关键词： Protocols Heuristic algorithms Computational modeling distributed algorithms Computer networks Electronic mail Network topology

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On the transformation capability of feasible mechanisms for programmable matter

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JOURNAL OF COMPUTER AND SYSTEM SCIENCES 2019年 102卷 18-39页

作者： Michail, Othon Skretas, George Spirakis, Paul G. Univ Liverpool Dept Comp Sci Ashton St Liverpool L69 3BX Merseyside England Comp Technol Inst Patras Greece Diophantus CTI Patras Greece Univ Patras CEID Patras Greece

We study theoretical models of programmable matter systems, consisting of n spherical modules kept together by magnetic or electrostatic forces and able to perform two minimal mechanical operations (movements): rotate and/or slide. The goal is for an initial shape A to transform to some target shape B by a sequence of movements. Most of the paper focuses on transformability (feasibility) questions. When only rotation is available, we prove that deciding whether two given shapes can transform to each other, is in P. Under the additional restriction of maintaining global connectivity, we prove inclusion in PSPACE and explore minimum seeds that can make otherwise infeasible transformations feasible. Allowing both rotations and slidings yields universality: any two connected shapes of the same order can be transformed to each other without breaking connectivity, in O (n(2)) sequential and O(n) parallel time (both optimal). We finally provide a type of distributed transformation. (C) 2019 Elsevier Inc. All rights reserved.

关键词： Programmable matter Transformation Reconfigurable robotics Shape formation Complexity distributed algorithms

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Multiagent Newton-Raphson Optimization Over Lossy Networks

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2019年第7期64卷 2983-2990页

作者： Bof, Nicoletta Carli, Ruggero Notarstefano, Giuseppe Schenato, Luca Varagnolo, Damiano Univ Padua Dept Informat Engn I-35131 Padua Italy Univ Bologna Dept Elect Elect & Informat Engn I-40126 Bologna Italy Lulea Univ Technol Dept Comp Sci Elect & Space Engn S-97187 Lulea Sweden

In this work, we study the problem of unconstrained convex optimization in a fully distributed multiagent setting, which includes asynchronous computation and lossy communication. In particular, we extend a recently proposed algorithm named Newton-Raphson consensus by integrating it with a broadcast-based average consensus algorithm, which is robust to packet losses. We show via the separation of time-scale principle that under mild conditions (i.e.. persistency of the agents activation and bounded consecutive communication failures), the proposed algorithm is provably locally exponentially stable with respect to the optimal global solution. Finally, we complement the theoretical analysis with numerical simulations and comparisons based on real datasets.

关键词： distributed algorithms optimization packet loss asynchronous communication wireless networks

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Scalable Formation Control of Double Integrator Agents: A distributed Observer Approach

Scalable Formation Control of Double Integrator Agents: A Di...

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SICE Annual Conference

作者： Djati Wibowo Djamari Muhamad Rausyan Fikri Faculty of Engineering and Technology Sampoerna University Indonesia

ISBN: (数字)9781728110899

ISBN: (纸本)9781728110905

This work studies formation control of double integrator agents where its formation size is scalable via a scaling factor (scalable formation). Previous works on scalable formation are limited to either fixed undirected graph or fixed directed graph with p-rooted graph condition. This work proposes a novel distributed algorithm for scalable formation based on a distributed observer to estimate agents' positions. The novel algorithm results in a new matrix, a Laplacian matrix with additional diagonal terms, where the desired formation pattern is embedded in this diagonal terms. With the proposed algorithm, only spanning tree condition is needed as the necessary and sufficient condition to achieve the scalable formation. Numerical examples are shown to illustrate the proposed method.

关键词： Sufficient conditions Laplace equations Tree graphs Instruments Directed graphs Observers distributed algorithms

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Efficient collective shape shifting and locomotion of massively-modular robotic structures

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AUTONOMOUS ROBOTS 2019年第1期43卷 97-122页

作者： Lengiewicz, Jakub Holobut, Pawel Polish Acad Sci Inst Fundamental Technol Res Warsaw Poland

We propose a methodology of planning effective shape shifting and locomotion of large-ensemble modular robots based on a cubic lattice. The modules are divided into two groups: fixed ones, that build a rigid porous frame, and mobile ones, that flow through the frame. Mobile modules which flow out of the structure attach to the frame, advancing its boundary. Conversely, a deficiency of mobile modules in other parts of the boundary is corrected by decomposition of the frame. Inside the structure, appropriate module flow is arranged to transport the modules in a desired direction, which is planned by a special distributed version of a maximum flow search algorithm. The method engages a volume of modules during reconfiguration, which is more efficient than common surface-flow approaches. Also, the proposed interpretation as a flow in porous media with moving boundaries seems particularly suitable for further development of more advanced global reconfiguration scenarios. The theoretical efficiency of the method is assessed, and then partially verified by a series of simulations. The method can be possibly also applied to a wider class of modular robots, not necessarily cubic-lattice-based.

关键词： Modular robots Self-reconfiguration Maximum flow search Programmable matter distributed algorithms

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SILP: A Stochastic Imitative Learning Protocol for Multi-Carrier Spectrum Access

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IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING 2019年第4期5卷 990-1003页

作者： Iellamo, Stefano Coupechoux, Marceau Khan, Zaheer Amadeus Airlines R&D Unit London TW6 2FL England Inst Polytech Paris Telecom Paris LTCI F-75013 Paris France Univ Oulu Ctr Wireless Commun Oulu 90120 Finland

Decentralized wireless networks require efficient channel access protocols to enable wireless nodes (WNs) to access dedicated frequency channels without any coordination. In this paper, we develop a distributed spectrum access protocol for the case where the WNs are equipped with multiple radio transceivers. We consider the case where the channels are identical and duly separated so that each of the users' antenna can access only one of the available channels. To model the competition amongst WNs, we formulate a particular multi-agent multi-carrier spectrum access game, where each WN has to decide at each iteration how many antennas and which frequency channels it has to access. To study the resulting equilibrium, we solve a multi-objective optimization problem and design a bi-level learning algorithm which is proven to converge toward a socially efficient and max-min fair equilibrium state.

关键词： Radio spectrum management distributed algorithms stochastic systems Pareto optimization

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distributed Framework for P2P Energy Sharing among Building Prosumers using Stackelberg Game

Distributed Framework for P2P Energy Sharing among Building ...

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IEEE Power and Energy Society General Meeting

作者： Kirtan Patel Sumedha Sharma Ashu Verma Cenre for Energy Sudies Indin Insiue of Technoogy DehiCenre for Energy Sudies Indin Insiue of Technoogy DehiCenre for Energy Sudies Indin Insiue of Technoogy Dehi

ISBN: (数字)9781728155081

ISBN: (纸本)9781728155081;9781728155098

Rising electricity demand, evolving consumption patterns and distributed generation have resulted in emergence of buildings as strategic players in the active distribution network. Owing to local generation, buildings have emerged as prosumers, capable of sharing energy within their community, also known as Peer to Peer (P2P) energy sharing. Accordingly, a P2P energy sharing model for building prosumers has been presented in this paper. The proposed scheme includes a Stackelberg game model consisting of building prosumers and system operator as players. Stackelberg equilibrium has been obtained, and its existence and uniqueness have been proved. A distributed algorithm has been formulated for optimizing internal trading prices and consumption while maximizing players' profits. In addition, detailed discussion has been presented on parameter tuning and its effect on performance of the proposed scheme. Further, an incentive re-distribution mechanism has been formulated for rewarding prosumer participation in peak hours. Simulation results depict effectiveness and verification of the proposed scheme.

关键词： Simulation Buildings Games Peer-to-peer computing distributed power generation distributed algorithms Tuning

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Multi-Hop Cooperative Computation Offloading for Industrial IoT-Edge-Cloud Computing Environments

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IEEE TRANSACTIONS ON PARALLEL AND distributed SYSTEMS 2019年第12期30卷 2759-2774页

作者： Hong, Zicong Chen, Wuhui Huang, Huawei Guo, Song Zheng, Zibin Sun Yat Sen Univ Sch Data & Comp Sci Guangzhou 510006 Guangdong Peoples R China Sun Yat Sen Univ Natl Engn Res Ctr Digital Life Guangzhou 510006 Guangdong Peoples R China Hong Kong Polytech Univ Dept Comp Hong Kong Peoples R China

The concept of the industrial Internet of things (IIoT) is being widely applied to service provisioning in many domains, including smart healthcare, intelligent transportation, autopilot, and the smart grid. However, because of the IIoT devices' limited onboard resources, supporting resource-intensive applications, such as 3D sensing, navigation, AI processing, and big-data analytics, remains a challenging task. In this paper, we study the multi-hop computation-offloading problem for the IIoT-edge-cloud computing model and adopt a game-theoretic approach to achieving Quality of service (QoS)-aware computation offloading in a distributed manner. First, we study the computation-offloading and communication-routing problems with the goal of minimizing each task & x0027;s computation time and energy consumption, formulating the joint problem as a potential game in which the IIoT devices determine their computation-offloading strategies. Second, we apply a free-bound mechanism that can ensure a finite improvement path to a Nash equilibrium. Third, we propose a multi-hop cooperative-messaging mechanism and develop two QoS-aware distributed algorithms that can achieve the Nash equilibrium. Our simulation results show that our algorithms offer a stable performance gain for IIoT in various scenarios and scale well as the device size increases.

关键词： Cloud computing Task analysis Quality of service Computational modeling Servers distributed algorithms Edge computing Computation offloading edge computing cloud computing game theory industrial IoT

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Online distributed Constrained Optimization Over General Unbalanced Digraphs

Online Distributed Constrained Optimization Over General Unb...

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Chinese Control and Decision Conference, CCDC

作者： Qing Yang Gang Chen School of Automation Chongqing University China

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

This paper studies the distributed online constrained optimization problem over a multiagent network, where each agent exchanges local information with neighbors on an unbalanced digraph with row-stochastic matrix. For solving such problem, an distributed online projection gradient algorithm is presented and the dynamic regret is adopted to measure its performance. With proper assumptions, we establish a dynamic-regret bound for each agent, which grows sublinearly as long as the increasing rate of the minimizer sequence' deviation lies in a certain range. Finally, a simulation example is provided to show the effectiveness of the proposed approach.

关键词： Heuristic algorithms Cost function Linear programming Benchmark testing distributed algorithms Automation

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distributed Algorithm for Principal Component Analysis Based on Power Method and Average Consensus Algorithm

Distributed Algorithm for Principal Component Analysis Based...

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Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)

作者： Norikazu Takahashi Mutsuki Oura Tsuyoshi Migita Graduate School of Natural Science and Technology Okayama University Okayama Japan

ISBN: (数字)9781728170862

ISBN: (纸本)9781728170879

Principal component analysis is one of the most important methods of multivariate analysis, and has been applied in a wide range of fields such as statistical analysis, machine learning, pattern recognition, signal processing, and communication. Recently, using the idea of multi-agent networks, distributed algorithms for principal component analysis have been proposed for the case where the data matrix is partitioned either row-wise or column-wise. In this paper, considering the case where the data matrix is partitioned both row-wise and column-wise, we propose a new algorithm that allows a multi-agent network to perform principal component analysis in a distributed manner. We also verify its validity by numerical experiments. The proposed algorithm is based on the power method for principal component analysis and the average consensus algorithm.

关键词： Signal processing algorithms distributed databases Consensus algorithm Signal processing Partitioning algorithms distributed algorithms Principal component analysis

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