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Local Prediction for Enhanced Convergence of distributed Optimization algorithms

IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2018年第4期5卷 1962-1975页

作者： Mai, Van Sy Abed, Eyad H. Univ Maryland Dept Elect & Comp Engn College Pk MD 20742 USA Univ Maryland Inst Syst Res College Pk MD 20742 USA

This paper studies distributed optimization problems where a network of agents seeks to minimize the sum of their private cost functions. We propose new algorithms based on the distributed subgradient method and the finite-time consensus protocol introduced by Sundaram and Hadjicostis (2007). In our first algorithm, the local optimization variables are updated cyclically through a subgradient step while the consensus variables follow a usual consensus protocol periodically interrupted by a predictive consensus estimate reset operation. For convex cost functions with bounded subgradients, this algorithm is guaranteed to converge to a certain range of the optimal value if using a constant step size or to the optimal value if a diminishing step size is in place. For differentiable cost functions whose sum is convex and has a Lipschitz continuous gradient, convergence to the optimal value can be ensured when using a constant step size, even if some of the individual cost functions are nonconvex. In addition, exponential convergence to the optimal solution is achieved when the global cost function is further assumed to be strongly convex. In these cases, the local optimization variables reach consensus in finite time, and then behave as they would under the centralized subgradient method applied to the global problem, except on a slower time scale. The second algorithm is specialized for the case of quadratic cost functions and converges in finite time to the optimal solution. Simulation examples are given to illustrate the algorithms.

关键词： distributed algorithms gradient methods graph theory network consensus

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distributed Partitioning algorithms for Locational Optimization of Multiagent Networks in SE(2)

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2018年第1期63卷 101-116页

作者： Bakolas, Efstathios Univ Texas Austin Dept Aerosp Engn & Engn Mech Austin TX 78712 USA

This paper is concerned with the development of distributed spatial partitioning algorithms for locational optimization problems involving networks of agents with planar rigid body dynamics subject to communication constraints. The domain of the problems we consider is a three-dimensional (3-D) nonflat manifold embedded in the state space of the agents, which we refer to as the terminal manifold. The approach we propose allows us to associate the partition of the 3-D terminal manifold, which is induced by a nonquadratic proximity metric and comprised of nonconvex cells, with a one-parameter family of partitions of 2-D flat manifolds, which are induced by (parametric) quadratic proximity metrics and comprised of convex polygonal cells. By exploiting the special structure of the parametric partitions, we develop distributed partitioning algorithms that converge in a finite number of steps. Subsequently, we utilize the solutions to the latter problems to solve a class of locational optimization problems over the terminal manifold. Numerical simulations that illustrate the capabilities of the proposed algorithms are also presented.

关键词： distributed algorithms locational optimization multi-agent networks partitioning algorithms

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Find Your Place: Simple distributed algorithms for Community Detection 28

Find Your Place: Simple Distributed Algorithms for Community...

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28th Annual ACM-SIAM Symposium on Discrete algorithms (SODA)

作者： Becchetti, Luca Clementi, Andrea. Natale, Emanuele Pasquale, Francesco Trevisan, Luca. Sapienza Univ Roma Rome Italy Univ Roma Tor Vergata Rome Italy Max Planck Inst Informat Saarbrucken Germany Univ Calif Berkeley Berkeley CA USA

ISBN: (纸本)9781611974782

Given an underlying graph, we consider the following dynamics: Initially, each node locally chooses a value in {-1, 1}, uniformly at random and independently of other nodes. Then, in each consecutive round, every node updates its local value to the average of the values held by its neighbors, at the same time applying an elementary, local clustering rule that only depends on the current and the previous values held by the node. We prove that the process resulting from this dynamics produces a clustering that exactly or approximately (depending on the graph) reflects the underlying cut in logarithmic time, under various graph models that exhibit a sparse balanced cut, including the stochastic block model. We also prove that a natural extension of this dynamics performs community detection on a regularized version of the stochastic block model with multiple communities. Rather surprisingly, our results provide rigorous evidence for the ability of an extremely simple and natural dynamics to address a computational problem that is non-trivial even in a centralized setting.

关键词： distributed algorithms Averaging Dynamics Community Detection Spectral Analysis Stochastic Block Models

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Continuous-Time distributed algorithms for Solving Linear Algebraic Equation 36

Continuous-Time Distributed Algorithms for Solving Linear Al...

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第36届中国控制会议

作者： Kai Cao Xianlin Zeng Yiguang Hong Key Laboratory of Systems and Control Institute of Systems ScienceChinese Academy of Sciences

ISBN: (纸本)9781538629185

In this paper,a multi-agent distributed continuous-time algorithm is proposed to solve a large-scale linear algebraic equation Ax = *** many existing results assuming each agent knows a few rows of A,the algorithm proposed in this paper assumes each agent knows a few columns of *** solve the linear algebraic equation,the problem is first converted to an optimization problem with a linear ***,a distributed continuous-time algorithm is designed based on the Lagrangian function of the optimization *** algorithm is proved to solve the linear algebraic equation with any initial condition via a Lyapunov *** example is presented to show the efficacy of the proposed algorithm.

关键词： distributed algorithms Multi-agent systems Linear algebraic equation Lagrangian function

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Efficient distributed algorithms suited for uncertain context

Efficient distributed algorithms suited for uncertain contex...

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作者： Anais Durand Communaute Universite Grenoble Alpes

学位级别：博士

distributed systems become increasingly wide and complex, while their usage extends to various domains (e. g., communication, home automation, monitoring, cloud computing). Thus, distributed systems are executed in diverse contexts. In this thesis, we focus on uncertain contexts, i. e., the context is not completely known a priori or is unsettled. More precisely, we consider two main kinds of uncertainty: processes that are not completely identified and the presence of faults. The absence of identification is frequent in large networks composed of massively produced and deployed devices. In addition, anonymity is often required for security and privacy. Similarly, large networks are exposed to faults (e. g., process crashes, wireless connection drop), but the service must remain available. This thesis is composed of four main contributions. First, we study the leader election problem in unidirectional rings of homonym processes, i. e., processes are identified but their ID is not necessarily unique. Then, we propose a silent self-stabilizing leader election algorithm for arbitrary connected network. This is the first algorithm under such conditions that stabilizes in a polynomial number of steps. The third contribution is a new stabilizing property designed for dynamic networks that ensures fast and gradual convergences after topological changes. We illustrate this property with a clock synchronizing algorithm. Finally, we consider the issue of concurrency in resource allocation problems. In particular, we study the level of concurrency that can be achieved in a wide class of resource allocation problem, i. e., the local resource allocation.

关键词： distributed algorithms fault-tolerance self-stabilization anonymity dynamic networks

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distributed algorithms for convexified bad data and topology error detection and identification problems

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2016年 83卷 241-250页

作者： Weng, Yang Ilic, Marija D. Li, Qiao Negi, Rohit Stanford Univ Dept Civil & Environm Engn Stanford CA 94305 USA Carnegie Mellon Univ Dept Elect & Comp Engn Pittsburgh PA 15213 USA Qualcomm Res New Jersey Bridgewater NJ 08807 USA

Large-scale smart grids call for online algorithms that are able to achieve the most accurate estimates. This paper shows how to achieve both the scalability and near globally optimal results for bad data and topology error detection and identification problems, by conducting fully distributed algorithms over convexified problem formulations. The proposed distributed decomposition is realized by (1) reducing a large network into much smaller network "cliques" which do not need extensive information exchange;(2) performing a Lagrangian dual decomposition in each clique and passing messages between cliques;and (3) conducting alternative coordinate descent optimization for robustness. To reduce the relaxation error in the convexification procedure, a nuclear norm penalty is added to approximate original problems. Finally, we propose a new metric to evaluate detection and identification results, which enables a system operator to characterize confidence for further system operations. We show that the proposed algorithms can be realized on IEEE test systems with improved accuracy in a short time. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Power systems Bad data and topology error Detection and identification distributed algorithms Convexification Semidefinite programming

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distributed algorithms for Joint Channel Access and Rate Control in Ultrasonic Intra-Body Networks

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IEEE-ACM TRANSACTIONS ON NETWORKING 2016年第5期24卷 3109-3122页

作者： Guan, Zhangyu Santagati, G. Enrico Melodia, Tommaso Northeastern Univ Dept Elect & Comp Engn Boston MA 02115 USA

Most research in body area networks to date has focused on traditional RF wireless communications, typically along the body surface. However, the core challenge of enabling networked intra-body communications through body tissues is substantially unaddressed. RF waves are in fact known to suffer from high absorption and to potentially lead to overheating of human tissues. In this paper, we consider the problem of designing optimal network control algorithms for distributed networked systems of implantable medical devices wirelessly interconnected by means of ultrasonic waves, which are known to propagate better than radio-frequency electromagnetic waves in aqueous media such as human tissues. Specifically, we propose lightweight, asynchronous, and distributed algorithms for joint rate control and stochastic channel access designed to maximize the throughput of ultrasonic intra-body area networks under energy constraints. We first develop (and validate through testbed experiments) a statistical model of the ultrasonic channel and of the spatial and temporal variability of ultrasonic interference. Compared to in-air radio frequency (RF), human tissues are characterized by a much lower propagation speed, which further causes unaligned interference at the receiver. It is therefore inefficient to perform adaptation based on instantaneous channel state information (CSI). Based on this model, we formulate the problem of maximizing the network throughput by jointly controlling the transmission rate and the channel access probability over a finite time horizon based only on a statistical characterization of interference. We then propose a fully distributed solution algorithm, and through both simulation and testbed results, we show that the algorithm achieves considerable throughput gains compared with traditional algorithms.

关键词： distributed algorithms intra-body area networks stochastic channel access ultrasonic communications

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distributed algorithms for barrier coverage using relocatable sensors

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distributed COMPUTING 2016年第5期29卷 361-376页

作者： Eftekhari, Mohsen Kranakis, Evangelos Krizanc, Danny Morales-Ponce, Oscar Narayanan, Lata Opatrny, Jaroslav Shende, Sunil Concordia Univ Dept Comp Sci & Software Engn Montreal PQ Canada Carleton Univ Sch Comp Sci Ottawa ON Canada Wesleyan Univ Dept Math & Comp Sci Middletown CT 06459 USA Chalmers Univ Technol Dept Comp Sci Gothenburg Sweden Rutgers State Univ Dept Comp Sci Camden NJ USA

We study the barrier coverage problem using relocatable sensor nodes. We assume each sensor can sense an intruder or event inside its sensing range. Sensors are initially located at arbitrary positions on the barrier and can move along the barrier. The goal is to find final positions for sensors so that the entire barrier is covered. In recent years, the problem has been studied extensively in the centralized setting. In this paper, we study a barrier coverage problem in the distributed and discrete setting. We assume that we have n identical sensors located at grid positions on the barrier, and that each sensor repeatedly executes a Look-Compute-Move cycle: based on what it sees in its vicinity, it makes a decision on where to move, and moves to its next position. We make two strong but realistic restrictions on the capabilities of sensors: they have a constant visibility range and can move only a constant distance in every cycle. In this model, we give the first two distributed algorithms that achieve barrier coverage for a line segment barrier when there are enough nodes in the network to cover the entire barrier. Our algorithms are synchronous, and local in the sense that sensors make their decisions independently based only on what they see within their constant visibility range. One of our algorithms is oblivious whereas the other uses two bits of memory at each sensor to store the type of move made in the previous step. We show that our oblivious algorithm terminates within steps with the barrier fully covered, while the constant-memory algorithm is shown to take steps to terminate in the worst case. Since any algorithm in which a sensor can only move a constant distance in one step requires steps on some inputs, our second algorithm is asymptotically optimal.

关键词： Barrier coverage Wireless relocatable sensors Autonomous mobile robots Optimal algorithms distributed algorithms

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A Real-Time Testbed for distributed algorithms: Evaluation of Average Consensus in Simulated Vehicular Ad Hoc Networks

A Real-Time Testbed for Distributed Algorithms: Evaluation o...

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作者： ALBIN CASPARSSON DAVID GARDTMAN Chalmers University of Technology

学位级别：硕士

Intelligent transportation systems consist of applications which use communication capabilities of vehicles to solve tasks that require cooperation with other vehicles. One of the possible applications is cooperative positioning, in which vehicles increase the accuracy of their positions by sharing positioning information with each other. Previous research has suggested using average consensus to share this information. Average consensus is a type of distributed algorithm that, in a system where each node performs a measurement of some value, can make all nodes reach agreement on the average of the set of measurements. This thesis evaluates the performance of average consensus algorithms in vehicular ad hoc networks. Full-scale experiments on vehicular systems are costly, but it is also not necessarily desired to fully simulate a vehicular system. This thesis presents a testbed where we opt to fully simulate the vehicular communication network. The vehicles that are part of the network can be simulated using either virtual nodes or a scaled down physical robot system. An 802.11p wireless network, which has been suggested for vehicular ad hoc networks, is simulated using the ns-3 network simulator. Addition- ally, some properties that cause the wireless network to be unreliable are simulated. Furthermore, in this thesis, three average consensus algorithms are implemented with some modifications to account for the properties of vehicular ad hoc networks. These algorithms are evaluated in the created testbed, in order to study their per- formance in such a network. We observe that consensus converges asymptotically in a simulation of randomly moving nodes, and that the consensus states of the nodes oscillate around the true average when new nodes are allowed to enter the system during consensus. The consensus converges to a state that does not necessarily co- incide exactly with the true average, which is to be expected since some packets are lost due the simulated wir

关键词： Average consensus Vehicular ad hoc networks Network simulation ns-3 Intelligent transportation systems distributed algorithms

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distributed Learning algorithms for Coordination in a Cognitive Network in Presence of Jammers 16

Distributed Learning Algorithms for Coordination in a Cognit...

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16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

作者： Sawant, Suneet Hanawal, Manjesh K. Darak, Sumit Kumar, Rohit Indian Inst Technol Dept EE Bombay 460076 Maharashtra India Indian Inst Technol IEOR Grp Bombay 460076 Maharashtra India IIIT Delhi Dept ECE New Delhi 110020 India NIT Delhi Dept ECE New Delhi 110040 India

ISBN: (纸本)9783903176003

Efficient utilization of licensed spectrum in the cognitive radio network is challenging due to lack of coordination among the Secondary Users (SUs). distributed algorithms proposed in the literature aim to maximize the network throughput by ensuring orthogonal channel allocation for the SUs. However, these algorithms work under the assumption that all the SUs faithfully follow the algorithms which may not always hold due to the decentralized nature of the network. Moreover, they are vulnerable to Denial of Service attacks. In this paper, we study distributed algorithms that are robust against malicious behavior (jamming attack). We consider jammers launching coordinated attack where they select non-overlapping channels in each time slot and can lead to significantly higher number of collisions for SUs than uncoordinated attack. We setup the problem as a multi player bandit and develop distributed learning algorithms. The analysis shows that when the SUs faithfully implement proposed algorithms, the regret is constant with high probability. We validate our claims through exhaustive synthetic experiments and also through a realistic USRP based experiments.

关键词： Jamming Signal processing algorithms distributed algorithms Throughput Channel allocation Channel estimation Knowledge engineering

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