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Securely Solving Linear Algebraic Equations in a distributed Framework Enhanced With Communication-Efficient algorithms

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2020年第3期7卷 1027-1042页

作者： Yin, Bo Shen, Wenlong Cao, Xianghui Cheng, Yu Li, Qing IIT Dept Elect & Comp Engn Chicago IL 60616 USA Southeast Univ Sch Automat Nanjing 210096 Peoples R China Symantec Corp Mountain View CA 94043 USA

Solving linear algebraic equations (a.k.a., an LAE problem) distributedly in a network with multiple agents has wide applications in distributed control, estimation, and signal processing. A consensus-based distributed computing framework is studied in this paper. Specifically, each agent knows only a subproblem of the LAE, i.e., a subset of all equations, and then all agents apply a consensus-based algorithm to update their estimates of the correct solution of the LAE problem iteratively. Under certain conditions, it has been shown that all the estimates converge to the exact solution exponentially fast. However, such a distributed paradigm is vulnerable to malicious behaviors in an adversarial environment. In this paper, we indicate a number of security threats in this process, and thus develop robust computing solutions against those attacks. With particular attention to low storage overhead, we develop a new alternating projection method to enhance the consensus algorithm. Furthermore, we design an innovative misbehavior detection mechanism by exploiting the homomorphic signature technique. Our method can detect misbehaving agents without the common, yet sometimes infeasible, assumption of local good majority. Another significant contribution presented in this paper is an original component dropping approach for mitigating the communication overhead during the consensus process. From both theoretical and engineering perspectives, we study how the consensus can still be reached when a big portion of elements in exchanged message vectors are dropped. In our preliminary numerical results, roughly 80% data transmission can be reduced per epoch at the expense of 35% extra epochs to reach the consensus, implying 73% reduction in terms of the communication overhead.

关键词： Outsourcing distributed computing distributed algorithms Optimization Monitoring Privacy Security distributed consensus linear algebraic equations security

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Brief Announcement: Perpetual Exploration of Triangular Grid by Myopic Oblivious Robots Without Chirality 26th

Brief Announcement: Perpetual Exploration of Triangular Grid...

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26th International Symposium on Stabilization, Safety, and Security of distributed Systems

作者： Das, Raja Goswami, Pritam Sau, Buddhadeb Jadavpur Univ Kolkata India

ISBN: (纸本)9783031744976;9783031744983

Exploration of different network topologies is one of the fundamental problems of distributed systems. The problem has been studied on networks like lines, rings, tori, rectangular grids, etc. In this work, we have considered a rectangle enclosed triangular grid (RETG). A RETG is a part of an infinite triangular grid and the part is enclosed by a rectangle whose one pair of parallel sides aligns with a family of parallel straight lines of the infinite triangular grid. We have studied the problem of perpetual exploration on a RETG using oblivious robots. We have considered the robots with limited visibility i.e. the robots are myopic. Infinite visibility becomes impractical for a very large network. Limited visibility is more practical than infinite visibility. The robots have neither any chirality nor any axis agreement. An algorithm is provided to explore the RETG perpetually without any collision. The algorithm works under a synchronous scheduler. The algorithm requires three robots with two hop visibility.

关键词： Myopic robot Autonomous robots Oblivious robot Triangular grid Perpetual exploration distributed algorithms

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Fast distributed Average Consensus algorithms Based on Advection-Diffusion Processes

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2010年第2期58卷 826-842页

作者： Sardellitti, Stefania Giona, Massimiliano Barbarossa, Sergio Univ Roma La Sapienza INFOCOM Dept I-00184 Rome Italy Univ Roma La Sapienza Dept Chem Engn I-00184 Rome Italy

distributed consensus algorithms have recently gained large interest in sensor networks as a way to achieve globally optimal decisions in a totally decentralized way, that is, without the need of sending all the data collected by the sensors to a fusion center. However, distributed algorithms are typically iterative and they suffer from convergence time and energy consumption. In this paper, we show that introducing appropriate asymmetric interaction mechanisms, with time-varying weights on each edge, it is possible to provide a substantial increase of convergence rate with respect to the symmetric time-invariant case. The basic idea underlying our approach comes from modeling the average consensus algorithm as an advection-diffusion process governing the homogenization of fluid mixtures. Exploiting such a conceptual link, we show how introducing interaction mechanisms among nearby nodes, mimicking suitable advection processes, yields a substantial increase of convergence rate. Moreover, we show that the homogenization enhancement induced by the advection term produces a qualitatively different scaling law of the convergence rate versus the network size with respect to the symmetric case.

关键词： Advection diffusion processes consensus algorithms convergence distributed algorithms sensor networks

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distributed Formation Control algorithms for QUAVs Based on Aggregative Games

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IEEE SYSTEMS JOURNAL 2023年第3期17卷 4419-4429页

作者： Deng, Zhenhua Luo, Jin Liu, Yangyang Yu, Weiyong Cent South Univ Sch Automat Changsha 410004 Peoples R China Beijing Inst Petrochem Technol Acad Artificial Intelligence Beijing 102617 Peoples R China

In this article, the formation problems of multiple quadrotor unmanned aerial vehicles (QUAVs) are studied. In contrast to existing results, the problems are investigated from the perspective of aggregative games (AGs). An interesting discovery is that the desired formation can be constituted by the Nash equilibrium of a quadratic AG. To realize the desired formation for QUAVs, we design two distributed game-based formation algorithms. With the developed algorithms, the QUAVs do not need to measure the (relative) positions and (relative) velocities of neighboring QUAVs, which differs from existing algorithms. By constructing suitable Lyapunov functions, we rigorously analyze the two formation algorithms. The first formation algorithm converges exponentially to the desired formation for the QUAVs without parameter uncertainties. The other algorithm converges asymptotically to the desired formation, even if the QUAVs contain uncertain parameters. Finally, we provide illustrative examples.

关键词： Formation control Heuristic algorithms Velocity measurement Switches Position measurement Games Control systems Aggregative games (AGs) distributed algorithms formation control multiagent systems quadrotor unmanned aerial vehicles (QUAVs)

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Impact of grid partitioning algorithms on combined distributed AC optimal power flow and parallel dynamic power grid simulation

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IET GENERATION TRANSMISSION & DISTRIBUTION 2020年第25期14卷 6133-6141页

作者： Kyesswa, Michael Murray, Alexander Schmurr, Philipp Cakmak, Hueseyin Kuehnapfel, Uwe Hagenmeyer, Veit Karlsruhe Inst Technol Inst Automat & Appl Informat Karlsruhe Germany

The complexity of most power grid simulation algorithms scales with the network size, which corresponds to the number of buses and branches in the grid. Parallel and distributed computing is one approach that can be used to achieve improved scalability. However, the efficiency of these algorithms requires an optimal grid partitioning strategy. To obtain the requisite power grid partitionings, the authors first apply several graph theory based partitioning algorithms, such as the Karlsruhe fast flow partitioner (KaFFPa), spectral clustering, and METIS. The goal of this study is an examination and evaluation of the impact of grid partitioning on power system problems. To this end, the computational performance of AC optimal power flow (OPF) and dynamic power grid simulation are tested. The partitioned OPF-problem is solved using the augmented Lagrangian based alternating direction inexact Newton method, whose solution is the basis for the initialisation step in the partitioned dynamic simulation problem. The computational performance of the partitioned systems in the implemented parallel and distributed algorithms is tested using various IEEE standard benchmark test networks. KaFFPa not only outperforms other partitioning algorithms for the AC OPF problem, but also for dynamic power grid simulation with respect to computational speed and scalability.

关键词： Newton method optimisation load flow IEEE standards power grids graph theory pattern clustering parallel algorithms power system simulation computational complexity optimal grid partitioning strategy spectral clustering power system problems computational performance partitioned OPF-problem augmented Lagrangian based alternating direction inexact Newton method partitioned dynamic simulation problem partitioned systems parallel algorithm distributed algorithms AC OPF problem grid partitioning algorithms combined distributed AC optimal power flow parallel dynamic power grid simulation distributed computing power grid simulation algorithms power grid partitionings parallel computing graph theory Karlsruhe fast flow partitioner KaFFPa METIS IEEE standard benchmark test networks

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Autonomous algorithms for centralized and distributed interference coordination: a virtual layer-based approach

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EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING 2014年第1期2014卷 1-20页

作者： Kasparick, Martin Wunder, Gerhard Fraunhofer Heinrich Hertz Inst D-10587 Berlin Germany Tech Univ Berlin D-10587 Berlin Germany

Interference mitigation techniques are essential for improving the performance of interference limited wireless networks. In this paper, we introduce novel interference mitigation schemes for wireless cellular networks with space division multiple access (SDMA). The schemes are based on a virtual layer that captures and simplifies the complicated interference situation in the network and that is used for power control. We show how optimization in this virtual layer generates gradually adapting power control settings that lead to autonomous interference minimization. Thereby, the granularity of control ranges from controlling frequency sub-band power via controlling the power on a per-beam basis, to a granularity of only enforcing average power constraints per beam. In conjunction with suitable short-term scheduling, our algorithms gradually steer the network towards a higher utility. We use extensive system-level simulations to compare three distributed algorithms and evaluate their applicability for different user mobility assumptions. In particular, it turns out that larger gains can be achieved by imposing average power constraints and allowing opportunistic scheduling instantaneously, rather than controlling the power in a strict way. Furthermore, we introduce a centralized algorithm, which directly solves the underlying optimization and shows fast convergence, as a performance benchmark for the distributed solutions. Moreover, we investigate the deviation from global optimality by comparing to a branch-and-bound-based solution.

关键词： Cellular interference management SDMA distributed algorithms Autonomous inter-cell coordination Power control Network utility maximization

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distributed Synchronous and Asynchronous algorithms for Semidefinite Programming With Diagonal Constraints

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2023年第2期68卷 1007-1022页

作者： Jiang, Xia Zeng, Xianlin Sun, Jian Chen, Jie Beijing Inst Technol Key Lab Intelligent Control & Decis Complex Syst Beijing Peoples R China Beijing Inst Technol Sch Automat Beijing Peoples R China Beijing Inst Technol Chongqing Innovat Ctr Chongqing 401120 Peoples R China Tongji Univ Sch Elect & Informat Engn Shanghai 200082 Peoples R China Minist Educ Beijing Inst Technol Beijing Adv Innovat Ctr Intelligent Robots & Syst Key Lab Biomimet Robots & Syst Beijing 100081 Peoples R China

This article develops distributed synchronous and asynchronous algorithms for the large-scale semidefinite programming with diagonal constraints, which has wide applications in combinatorial optimization, image processing, and community detection. The information of the semidefinite programming is allocated to multiple interconnected agents such that each agent aims to find a solution by communicating to its neighbors. Based on the low-rank property of solutions and the Burer-Monteiro factorization, we transform the original problem into a distributed optimization problem over unit spheres to reduce variable dimensions and ensure positive semidefiniteness without involving semidefinite projections, which are computationally expensive. For the distributed optimization problem, we propose distributed synchronous and asynchronous algorithms, both of which reduce computational burden and storage space compared with existing centralized algorithms. Specifically, the distributed synchronous algorithm almost surely escapes strict saddle points and converges to the set of optimal solutions to the optimization problem. In addition, the proposed distributed asynchronous algorithm allows communication delays and converges to critical points to the optimization problem under mild conditions. By applying the proposed algorithms to image segmentation, we illustrate the efficiency and convergence performance of the two proposed algorithms.

关键词： Optimization Symmetric matrices distributed algorithms Programming Costs Convergence Sun distributed optimization low-rank matrices semidefinite programming (SDP) with diagonal constraints synchronous and asynchronous algorithms

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Understanding complex, real-world systems through asynchronous, distributed decision-making algorithms

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JOURNAL OF SYSTEMS AND SOFTWARE 2001年第2期58卷 153-167页

作者： Ghosh, S Stevens Inst Technol Dept Elect & Comp Engn Secure Network Design Lab Hoboken NJ 07030 USA

Traditionally, the underlying decision-making algorithms for most real-world systems have been centralized. The term, real-world, refers to systems under computer control that relate to everyday life, are beneficial to the society in the large, and are generally large-scale in scope. Examples include AT&T's dynamic non-hierarchical routing (DNHR) for routing telephone calls, the North American advanced train control system (ATCS) for routing railways, the Swiss banking system (SIC), and inventory management algorithms. While centralized algorithms are simple, easy to conceive and implement, they execute sequentially on uniprocessors and are slow. In addition, by their very nature, centralized algorithms are highly susceptible to natural and artificial disasters. Synchronous distributed algorithms constitute a performance improvement over centralized algorithms, and have been used in fault simulation within the discipline of computer-aided design of digital systems and in matrix manipulations. However, their performance is limited due to frequent inherent synchronizations. This paper critically examines the nature of large-scale, real-world systems and observes that, fundamentally, most complex systems are composed of entities - concurrent, independent, and self-contained units of decision-making, that interact with each other, asynchronously. This paper presents a new class of algorithms asynchronous, distributed, decision-making (ADDM) algorithms, to constitute the underlying control of such systems. While ADDM algorithms are closely related to autonomous decentralized systems (ADS) in the principal elements, their characteristics and boundaries are defined rigorously. While ADDM algorithms are difficult to conceive, design, and implement, they constitute the natural and logical choice for systems control, and hold the promise of extracting the maximal parallelism inherent in these systems. In addition, in principle, true asynchronous systems can be described accur

关键词： systems physical processes asynchronous interactions distributed algorithms real-world systems

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Input-Output Performance of Linear-Quadratic Saddle-Point algorithms With Application to distributed Resource Allocation Problems

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2020年第5期65卷 2032-2045页

作者： Simpson-Porco, John W. Poolla, Bala Kameshwar Monshizadeh, Nima Dorfler, Florian Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada Swiss Fed Inst Technol Zurich Automat Control Lab CH-8092 Zurich Switzerland Univ Groningen Engn & Technol Inst NL-9747 AG Groningen Netherlands

Saddle-point or primal-dual methods have recently attracted renewed interest as a systematic technique to design distributed algorithms, which solve convex optimization problems. When implemented online for streaming data or as dynamic feedback controllers, these algorithms become subject to disturbances and noise;convergence rates provide incomplete performance information, and quantifying input-output performance becomes more important. We analyze the input-output performance of the continuous-time saddle-point method applied to linearly constrained quadratic programs, providing explicit expressions for the saddle-point $\mathcal {H}_2$ norm under a relevant input-output configuration. We then proceed to derive analogous results for regularized and augmented versions of the saddle-point algorithm. We observe some rather peculiar effects-a modest amount of regularization significantly improves the transient performance, while augmentation does not necessarily offer improvement. We then propose a distributed dual version of the algorithm, which overcomes some of the performance limitations imposed by augmentation. Finally, we apply our results to a resource allocation problem to compare the input-output performance of various centralized and distributed saddle-point implementations and show that distributed algorithms may perform as well as their centralized counterparts.

关键词： Optimization Heuristic algorithms Convergence Resource management Standards distributed algorithms Transient analysis distributed algorithms input-output performance primal-dual dynamics resource allocation saddle-point methods system norms

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Exact distributed Load Centrality Computation: algorithms, Convergence, and Applications to Distance Vector Routing

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IEEE TRANSACTIONS ON PARALLEL AND distributed SYSTEMS 2020年第7期31卷 1693-1706页

作者： Maccari, Leonardo Ghiro, Lorenzo Guerrieri, Alessio Montresor, Alberto Lo Cigno, Renato Univ Venice I-30123 Venice Italy Univ Trento I-38122 Trento Italy SpazioDati Srl I-56021 Cascina Italy Univ Brescia I-25121 Brescia Italy

Many optimization techniques for networking protocols take advantage of topological information to improve performance. Often, the topological information at the core of these techniques is a centrality metric such as the Betweenness Centrality (BC) index. BC is, in fact, a centrality metric with many well-known successful applications documented in the literature, from resource allocation to routing. To compute BC, however, each node must run a centralized algorithm and needs to have the global topological knowledge;such requirements limit the feasibility of optimization procedures based on BC. To overcome restrictions of this kind, we present a novel distributed algorithm that requires only local information to compute an alternative similar metric, called Load Centrality (LC). We present the new algorithm together with a proof of its convergence and the analysis of its time complexity. The proposed algorithm is general enough to be integrated with any distance vector (DV) routing protocol. In support of this claim, we provide an implementation on top of Babel, a real-world DV protocol. We use this implementation in an emulation framework to show how LC can be exploited to reduce Babel's convergence time upon node failure, without increasing control overhead. As a key step towards the adoption of centrality-based optimization for routing, we study how the algorithm can be incrementally introduced in a network running a DV routing protocol. We show that even when only a small fraction of nodes participate in the protocol, the algorithm accurately ranks nodes according to their centrality.

关键词： Routing protocols Measurement Routing Indexes distributed algorithms Network topology Multi-hop networks mesh networks ad-hoc networks bellman-ford load centrality distributed algorithms failure recovery

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