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distributed algorithm design for constrained resource allocation problems with high-order multi-agent systems

AUTOMATICA 2022年 144卷

作者： Deng, Zhenhua Chen, Tao Cent South Univ Sch Automat Changsha 410075 Peoples R China

This paper studies distributed resource allocation problems of multi-agent systems, where the decisions of agents are subject to inequality network resource constraints and local inequality constraints. Compared with well-known resource allocation problems, our problem considers the high-order dynamics of agents. Without involving the control of high-order dynamics, existing distributed resource allocation algorithms cannot deal with our problem. Meanwhile, the high-order dynamics together with the inequality constraints makes it difficult to design and analyze distributed resource allocation algorithms, because the outputs of agents cannot be decided by their inputs directly and the optimal decisions of agents must satisfy the inequality constraints. In order to control the high -order agents to accomplish the resource allocation tasks autonomously, a distributed algorithm is designed by state feedback, gradient descent and primal-dual methods. Moreover, the convergence of the algorithm is analyzed by convex analysis and Lyapunov stability theory. With the algorithm, the high-order agents converge to the optimal allocation. Finally, numerical simulations verify the effectiveness of the algorithm. (C) 2022 Published by Elsevier Ltd.

关键词： Resource allocation Inequality constraints High-order multi -agent systems distributed algorithms Cyber-physical systems

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Optimal partitioning in distributed state estimation considering a modified convergence criterion 4

Optimal partitioning in distributed state estimation conside...

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4th International Conference on Smart Energy Systems and Technologies (SEST)

作者： Asefi, Sajjad Gryazina, Elena Leite, Helder Skolkovo Inst Sci & Technol Ctr Energy Sci & Technol Moscow Russia Univ Porto Elect Engn Dept Porto Portugal

ISBN: (纸本)9781728176604

distributed state estimation (DSE) is considered as a more robust and reliable alternative for centralized state estimation (CSE) in power system. Especially, taking into account the future power grid, so called smart grid in which bi-directional transfer of energy and information happens, and renewable energy sources with huge indeterminacy are applied more than before. Combining the mentioned features and complexity of the power network, there is a high probability that CSE face problems such as communication bottleneck or security/reliability issues. So, DSE has the potential to be considered as a solution to solve the mentioned issues. In this paper, first, a modified convergence criterion is proposed and has been tested for different approaches of DSE problem, considering the most important factors such as iteration number, convergence rate, and data needed to be transferred to/from each area. Then, an optimal partitioning technique has been implemented for clustering the system into different areas. Besides the detailed analysis and comparison of recent DSE methods, the proposed partitioning method's effectiveness and scalability has been shown in this paper.

关键词： distributed algorithms optimization partitioning power system control state estimation

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distributed Domain Generation for Large-Scale Scientific Computing 20

Distributed Domain Generation for Large-Scale Scientific Com...

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20th International Symposium on Parallel and distributed Computing (ISPDC)

作者： Ertl, Christoph Mundani, Ralf-Peter Tech Univ Munich Chair Computat Modeling & Simulat Munich Germany Univ Appl Sci Grisons Swiss Inst Informat Sci Chur Switzerland

ISBN: (纸本)9781665432818

In this work, we present methods for distributed domain generation within the constraints of our decentral domain management concept. Here, all participating actors only have knowledge of their immediate neighbours, which are defined by geometric and hierarchical relations between nodes that represent subsets of the computational domain. We generate this domain following a hierarchical spacetree refinement. First, an initial tree is generated on every participating process. Second, this tree is distributed following a space-filling curve linearisation locally. Every process is assigned at least one leaf node of the initial tree, which acts as a starting point for the subsequent domain generation. From here, every process independently refines a subdomain using a decomposition method, which transforms a triangular surface-based geometry description into a volume-based one, using increasingly complex intersection tests. The resulting domain tree is distributed, yet neighbourhood references of neighbouring subtrees are not resolved. We combine the resolution of these relations with a 2:1 tree balancing, which involves the transfer of the surface of neighbouring subtrees. We provide results of a domain generation testcase, using an input geometry with 84,072 triangles on up to 896 processes of the CoolMUC-2 cluster segment of LRZ's Linux Cluster System. Here, we bring down the overall time it takes to generate an adaptively refined and balanced octree with depth d = 7 from 5.5 hours on one process to two seconds on 896 processes.

关键词： Large-scale scientific computing parallel algorithms distributed algorithms distributed systems distributed domain generation spacetrees

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A distributed Dual Proximal Algorithm for Non-Smooth Composite Constrained Optimization and Its Application 40

A Distributed Dual Proximal Algorithm for Non-Smooth Composi...

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40th Chinese Control Conference (CCC)

作者： Ran, Liang Hu, Jinhui Liu, Hongli Li, Huaqing Southwest Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Coll Elect & Informat Engn Chongqing 400715 Peoples R China

ISBN: (纸本)9789881563804

distributed optimization is a promising prospect that shows high potential in various applications, such as machine learning, power systems and others. This paper studies a class of constrained composite optimization problems over a network of agents, in which the local cost functions that are privately maintained by agents can be split into a strongly convex term and a convex (or possibly non-smooth) one. To tackle this problem in a distribute manner, a class of synchronous distributed algorithms based on dual proximal methods (SynDis-DuPro) is presented, and its asynchronous version (AsynDis-DuPro) without the global clock is developed as well. Under the proposed schemes, each agent in the network not only possesses the individual step-sizes, but also conducts local computation and communication without leaking its private information. In addition, the practicability and effectiveness of the proposed algorithms are demonstrated by the simulations on distributed energy resources coordination (DERC) based on power systems.

关键词： Convex optimization multi-agent systems distributed algorithms non-smooth constrained optimization problems

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Greedy-based distributed algorithms for green traffic routing

Greedy-based distributed algorithms for green traffic routin...

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International Conference on Computer Communications and Networks (ICCCN)

作者： Yunlong Song Min Liu University of Chinese Academy of Sciences Beijing P.R. China Institute of Computing Technology Chinese Academy of Sciences

Green networking has become a hot research area in recent years. Most works just focus on centralized algorithms, where a central controller is used to collect all the information of the network and compute the energy aware traffic routing. However, these centralized algorithms only fit to the scenario when the network is not large and assume that all the network's information can be timely collected. When the above condition is not satisfied, the centralized algorithms will not work any more. In this paper, we study the basic principles of energy aware traffic routing and use them to explore a greedy-based distributed algorithm. The evaluation shows that our algorithm can reduce more energy consumption (almost 15%) than the existing distributed algorithms.

关键词： Density measurement Power system measurements Routing Power demand distributed algorithms Green products Routing protocols

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DiBB: Distributing Black-Box Optimization

DiBB: Distributing Black-Box Optimization

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Genetic and Evolutionary Computation Conference (GECCO)

作者： Cuccu, Giuseppe Rolshoven, Luca Vorpe, Fabien Cudre-Mauroux, Philippe Glasmachers, Tobias Univ Fribourg Exascale Infolab Fribourg Switzerland Ruhr Univ Bochum Theory ML Grp Bochum Germany

ISBN: (纸本)9781450392372

DiBB (for Distributing Black-Box) is a meta-algorithm and framework that addresses the decades-old scalability issue of Black-Box Optimization (BBO), including Evolutionary Computation. Algorithmically, it does so by creating out-of-the-box a Partially Separable (PS) version of any existing black-box algorithm. This is done by leveraging expert knowledge about the task at hand to define blocks of parameters expected to have significant correlation, such as weights entering a same neuron/layer in a neuroevolution application. DiBB distributes the computation to a set of machines without further customization, while still retaining the advanced features of the underlying BBO algorithm, such as scale invariance and step-size adaptation, which are typically lost in recent distributed ES implementations. This is achieved by instantiating a separate instance of the underlying base algorithm for each block, running on a dedicated machine, with DiBB handling communication and constructing complete individuals for evaluation on the original task. DiBB's performance scales constantly with the number of parameter-blocks defined, which should allow for unprecedented applications on large clusters. Our reference implementation (Python, on GitHub and PyPI) demonstrates a 5x speed-up on COCO/BBOB using our new PS-CMA-ES. We also showcase a neuroevolution application (11 590 weights) on the PyBullet Walker2D with our new PS-LM-MA-ES.

关键词： Black-Box Optimization distributed algorithms Parallelization Evolution Strategies Neuroevolution

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A distributed Algorithm for Overlapped Community Detection in Large-Scale Networks

A Distributed Algorithm for Overlapped Community Detection i...

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International Conference on COMmunication Systems and NETworkS (COMSNETS)

作者： Saha, Dibakar Mandal, Partha Sarathi Indian Inst Technol Guwahati Dept Math Gauhati Assam India

ISBN: (纸本)9781728191270

Overlapped community detection in social networks has become an important research area with the increasing popularity and complexity of the networks. Most of the existing solutions are either centralized or parallel algorithms, which are computationally intensive - require complete knowledge of the entire network. But it isn't easy to collect entire network data because the size of the actual network may be prohibitively large. It may result from either privacy concerns (users of a social network may be unwilling to reveal their social links) or technological impediments (implementation of an efficient web crawler). Performing in-network computation solves both problems utilizing the computational capability of the individual nodes of the network. Simultaneously, nodes communicate and share data with their neighbours via message passing, which may go a long way toward mitigating individual nodes' privacy concerns in the network. All the concerns mentioned above motivated us to design a decentralized or distributed technique to detect overlapped communities in a large-scale network. It is desirable because this technique does not offer a single point of failure, and the system as a whole can continue to function even when many of the nodes fail. To overcome the disadvantages of the existing solutions, in this paper, we address the overlapped community detection problem for large-scale networks. We present an efficient distributed algorithm, named DOCD, to identify the overlapped communities in the network. The efficiency of DOCD algorithm is verified with extensive simulation study on some networks such as, Dolphin, Zachary karate club, Football club, and Facebook ego networks. We show that DOCD algorithm is capable of keeping the asymptotically same results with the existing classical centralized algorithms [1]-[5] in terms of community modularity and the number of identified communities. The DOCD algorithm can also efficiently identify the overlapped nodes and ove

关键词： Overlapped Community Community Detection Social Networks Large-Scale Networks distributed algorithms

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distributed Coloring and the Local Structure of Unit-Disk Graphs 1

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17th International Symposium on algorithms and Experiments for Wireless Sensor Networks (ALGOSENSORS)

作者： Esperet, Louis Julliot, Sebastien de Mesmay, Arnaud Univ Grenoble Alpes CNRS Lab G SCOP Grenoble France Univ Gustave Eiffel CNRS LIGM ESIEE Paris F-77454 Marne La Vallee France

ISBN: (数字)9783030892401

ISBN: (纸本)9783030892395;9783030892401

Coloring unit-disk graphs efficiently is an important problem in the global and distributed settings, with applications in radio channel assignment problems when the communication relies on omnidirectional antennas of the same power. In this context it is important to bound not only the complexity of the coloring algorithms, but also the number of colors used. In this paper, we consider two natural distributed settings. In the location-aware setting (when nodes know their coordinates in the plane), we give a constant time distributed algorithm coloring any unit-disk graph G with at most (3 + epsilon)omega(G) + 6 colors, for any constant epsilon > 0, where omega(G) is the clique number of G. This improves upon a classical 3-approximation algorithm for this problem, for all unit-disk graphs whose chromatic number significantly exceeds their clique number. When nodes do not know their coordinates in the plane, we give a distributed algorithm in the LOCAL model that colors every unit-disk graph G with at most 5.68.(G) colors in O(log(3) log n) rounds. Moreover, when omega(G) = O(1), the algorithm runs in O(log* n) rounds. This algorithm is based on a study of the local structure of unit-disk graphs, which is of independent interest. We conjecture that every unit-disk graph G has average degree at most 4 omega(G), which would imply the existence of a O(log n) round algorithm coloring any unit-disk graph G with (approximatively) 4 omega(G) colors.

关键词： distributed algorithms Graph coloring Unit-disk graphs

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Reaching Consensus for Asynchronous distributed Key Generation 21

Reaching Consensus for Asynchronous Distributed Key Generati...

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40th ACM SIGACT-SIGOPS Symposium on Principles of distributed Computing (PODC)

作者： Abraham, Ittai Jovanovic, Philipp Maller, Mary Meiklejohn, Sarah Stern, Gilad Tomescu, Alin VMware Res Herzliyya Israel UCL London England Ethereum Fdn London England Google London England Hebrew Univ Jerusalem Jerusalem Israel VMware Res Palo Alto CA USA

We give a protocol for Asynchronous distributed Key Generation (A-DKG) that is optimally resilient (can withstand f (n(3)) expected communication complexity, and assumes only the existence of a PKI. Prior to our work,... 详细信息

ISBN: (纸本)9781450385480

We give a protocol for Asynchronous distributed Key Generation (A-DKG) that is optimally resilient (can withstand f < n/3 sfaulty parties), has a constant expected number of rounds, has <(O)over tilde>(n(3)) expected communication complexity, and assumes only the existence of a PKI. Prior to our work, the best A-DKG protocols required Omega (n) expected number of rounds, and Q (n(4)) expected communication. Our A-DKG protocol relies on several building blocks that are of independent interest. We define and design a Proposal Election (PE) protocol that allows parties to retrospectively agree on a valid proposal after enough proposals have been sent from different parties. With constant probability the elected proposal was proposed by a nonfaulty party. In building our PE protocol, we design a Verifiable Gather protocol which allows parties to communicate which proposals they have and have not seen in a verifiable manner. The final building block to our A-DKG is a Validated Asynchronous Byzantine Agreement (VABA) protocol. We use our PE protocol to construct a VABA protocol that does not require leaders or an asynchronous DKG setup. Our VABA protocol can be used more generally when it is not possible to use threshold signatures.

关键词： distributed algorithms cryptographic protocols Byzantine fault tolerance distributed key generation consensus leader election

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Message complexity of distributed algorithms revisited

Message complexity of distributed algorithms revisited

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International Conference on Parallel distributed and Grid Computing (PDGC)

作者： Behnish Mann Alex Arvavid University of Northern British Columbia Prince George Canada

distributed systems offer many features such as resource sharing, scalability, fault tolerance and reliability. Several distributed algorithms have been proposed in literature to solve fundamental problems such as mutual exclusion and leader election in distributed systems. When more than one algorithm is invented to solve the same problem particularly in asynchronous distributed systems, their performance is compared mostly based on the message complexity. This paper reviews the concept of message complexity and offers more clarity by studying the performance of the two most popular distributed algorithms - Ricart-Agrawala's algorithm and Raymond algorithm designed to solve the mutual exclusion problem. The paper has four main contributions (i) observes how the message complexity is understood and computed in the asynchronous distributed system so far and exposes its elusiveness; (ii) offers a more suitable definition of message complexity; (iii) briefly presents the simulator designed to study the performance of the distributed algorithms using the refined metric; and finally (iv) discusses about the simulation study to illustrate the significance and usefulness of the proposed metric.

关键词： Complexity theory Topology Algorithm design and analysis Network topology distributed algorithms Measurement Engines

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