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IEEE International Conference on Civil Aviation Safety and Information Technology (ICCASIT)

作者： Shufei Qi Wenyi Sun Yonggang Zong Ocean Department Binzhou Polytechnic Binzhou China

ISBN: (数字)9798350389418

ISBN: (纸本)9798350389425

This paper proposes a remote monitoring and decision-making system for intelligent ships based on edge computing and distributed algorithms. Relying on the high bandwidth and low latency characteristics of 5 G communication, real-time data processing and remote monitoring of ship operation status are realized. The system localizes a large amount of sensor data through edge computing, and combines distributed algorithms to improve data fusion and decisionmaking efficiency. Data transmission supported by 5G communication provides technical guarantee for seamless connection between ships and shore-based monitoring centers. Through real-time analysis of ship sensor data, the system can predict potential faults and optimize navigation strategies. Model simulation results show that the distributed algorithm based on edge computing has significant advantages in improving data processing speed, reducing decision response time by 15% and improving monitoring accuracy by 8.5%. This study provides technical support for remote monitoring and autonomous decision-making of intelligent ships, and verifies the broad application prospects of $\mathbf{5 G}$ communication in the field of maritime communications.

关键词： Navigation Decision making distributed databases Real-time systems Safety Data communication Marine vehicles distributed algorithms Remote monitoring Edge computing

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distributed Detection of Malicious Attacks on Consensus algorithms with Applications in Power Networks

Distributed Detection of Malicious Attacks on Consensus Algo...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Sourav Patel Vivek Khatana Govind Saraswat Murti V. Salapaka University of Minnesota Minneapolis USA National Renewable Energy Laboratory Golden CO USA

ISBN: (数字)9781728159539

ISBN: (纸本)9781728159546

Consensus-based distributed algorithms are well suited for coordination among agents in a cyber-physical system. These distributed schemes, however, suffer from their vulnerability to cyber attacks that are aimed at manipulating data and control ow. In this article, we present a novel distributed method for detecting the presence of such intrusions for a distributed multi-agent system following ratio consensus. We employ a Max-Min protocol to develop low cost, easy to implement detection strategies where each participating node detects the intrusion independently, eliminating the need for a trusted certifying agent in the network. The effectiveness of the detection method is demonstrated by numerical simulations on a 1000 node network to demonstrate the efficacy and simplicity of implementation.

关键词： Directed graphs Cyber-physical systems Consensus algorithm Government distributed algorithms Topology Multi-agent systems

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Joint Sensing and Power Allocation in Nonconvex Cognitive Radio Games: Nash Equilibria and distributed algorithms

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IEEE TRANSACTIONS ON INFORMATION THEORY 2013年第7期59卷 4626-4661页

作者： Scutari, Gesualdo Pang, Jong-Shi SUNY Buffalo Dept Elect Engn Buffalo NY 14051 USA Univ Illinois Dept Ind & Enterprise Syst Engn Urbana IL 61801 USA

In this paper, we propose a novel class of Nash problems for cognitive radio (CR) networks, modeled as Gaussian frequency-selective interference channels, wherein each secondary user (SU) competes against the others to maximize his own opportunistic throughput by choosing jointly the sensing duration, the detection thresholds, and the vector power allocation. The proposed general formulation allows us to accommodate several (transmit) power and (deterministic/probabilistic) interference constraints, such as constraints on the maximum individual and/or aggregate (probabilistic) interference tolerable at the primary receivers. To keep the optimization as decentralized as possible, global (coupling) interference constraints are imposed by penalizing each SU with a set of time-varying prices based upon his contribution to the total interference;the prices are thus additional variable to optimize. The resulting players' optimization problems are nonconvex;moreover, there are possibly price clearing conditions associated with the global constraints to be satisfied by the solution. All this makes the analysis of the proposed games a challenging task;none of classical results in the game theory literature can be successfully applied. The main contribution of this paper is to develop a novel optimization-based theory for studying the proposed nonconvex games;we provide a comprehensive analysis of the existence and uniqueness of a standard Nash equilibrium, devise alternative best-response based algorithms, and establish their convergence. Some of the proposed algorithms are totally distributed and asynchronous, whereas some others require limited signaling among the SUs (in the form of consensus algorithms) in favor of better performance;overall, they are thus applicable to a variety of CR scenarios, either cooperative or noncooperative, which allows the SUs to explore the existing tradeoff between signaling and performance.

关键词： Cognitive radio distributed algorithms game theory quasi-Nash equilibrium spectrum sensing variational inequalities

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On the Locality of the Lovász Local Lemma 25

On the Locality of the Lovász Local Lemma

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Proceedings of the 57th Annual ACM Symposium on Theory of Computing

作者： Peter Davies-Peck Durham University Durham United Kingdom

ISBN: (纸本)9798400715105

The Lovász Local Lemma is a versatile result in probability theory, characterizing circumstances in which a collection of n ‘bad events’, each occurring with probability at most p and dependent on a set of underlying random variables, can be avoided. It is a central tool of the probabilistic method, since it can be used to show that combinatorial objects satisfying some desirable properties must exist. While the original proof was existential, subsequent work has shown algorithms for the Lovász Local Lemma: that is, in circumstances in which the lemma proves the existence of some object, these algorithms can constructively find such an object. One main strand of these algorithms, which began with Moser and Tardos’s well-known result (JACM 2010), involves iteratively resampling the dependent variables of satisfied bad events until none remain *** this paper, we present a novel analysis that can be applied to resampling-style Lovász Local Lemma algorithms. This analysis shows that an output assignment for the dependent variables of most events can be determined only from O(loglog1/p n)-radius local neighborhoods, and that the events whose variables may still require resampling can be identified from these neighborhoods. This allows us to improve randomized complexities for the constructive Lovász Local Lemma (with polynomial criterion) in several parallel and distributed *** particular, we obtain a LOCAL algorithm with O(loglog1/p n) node-averaged complexity (while matching the O(log1/p n) worst-case complexity of Chung, Pettie, and Su), an algorithm for the LCA and VOLUME models requiring dO(loglog1/p n) probes per query, and an O(logloglog1/p n)-round algorithm for the CONGESTED CLIQUE, linear space MPC, and Heterogenous MPC models.

关键词： distributed algorithms

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Tutorial: Consensus algorithms from Classical to Blockchain: Quickly Program, Configure, Run, and Check

Tutorial: Consensus Algorithms from Classical to Blockchain:...

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International Conference on distributed Computing Systems Workshop

作者： Yanhong A. Liu Scott D. Stoller Stony Brook University

ISBN: (数字)9798350354713

ISBN: (纸本)9798350354720

This tutorial examines well-known algorithms for distributed consensus problems, from classical consensus to blockchain consensus. We discuss exact algorithms that are high-level as in pseudocode and directly executable as programs at the same time, focusing on how to quickly program, configure, run, and check these algorithms as well as distributed algorithms and systems in general.

关键词： Conferences Focusing Tutorials Consensus algorithm Blockchains distributed computing distributed algorithms

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Can Model Checking Assure, distributed Autonomous Systems Agree? An Urban Air Mobility Case Study

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2020年第12期11卷 61-72页

作者： Gupta, Anubhav Bhattacharyya, Siddhartha Vadivel, S. Florida Inst Technol Dept Comp Sci & Engn Melbourne FL 32904 USA BITS Pilani Dept Comp Sci Dubai Campus Dubai U Arab Emirates

Advancement in artificial intelligence, internet of things and information technology have enabled the delegation of execution of autonomous services to autonomous systems for civil applications. It is envisioned, that with an increase in the demand for autonomous systems, the decision making associated in the execution of the autonomous services will be distributed, with some of the responsibility in decision making, shifted to the autonomous systems. Thus, it is of utmost importance that we assure the correctness of distributed protocols, that multiple autonomous systems will follow, as they interact with each other in providing the service. Towards this end, we discuss our proposed framework to model, analyze and assure the correctness of distributed protocols executed by autonomous systems to provide a service. We demonstrate our approach by formally modeling the behavior of autonomous systems that will be involved in providing services in the Urban Air Mobility framework that enables air taxis to transport passengers.

关键词： Formal methods autonomous systems distributed algorithms assurance for distributed protocols distributed protocol modeling and verification distributed autonomous systems

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Smooth Dynamics for distributed Constrained Optimization With Heterogeneous Delays

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IEEE CONTROL SYSTEMS LETTERS 2020年第3期4卷 626-631页

作者： Li, Mengmou Yamashita, Shunya Hatanaka, Takeshi Chesi, Graziano Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China Tokyo Inst Technol Sch Engn Tokyo 1528550 Japan

This letter investigates the distributed constrained optimization problem under inter-agent communication delays from the perspective of passivity. First, we propose a continuous-time algorithm for distributed constrained optimization with general convex objective functions. The asymptotic stability under general convexity is guaranteed by the phase lead compensation. The inequality constraints are handled by adopting a projection-free generalized Lagrangian, whose primal-dual gradient dynamics preserves passivity and smoothness, enabling the application of the LaSalle's invariance principle in the presence of delays. Then, we incorporate the scattering transformation into the proposed algorithm to enhance the robustness against unknown and heterogeneous communication delays. Finally, a numerical example of a matching problem is provided to illustrate the results.

关键词： Delays Optimization Heuristic algorithms Linear programming Lead Convergence distributed algorithms distributed optimization passivity delays

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Energy-Efficient Leader Election in IoT Networks: A Cloud Storage Perspective

Energy-Efficient Leader Election in IoT Networks: A Cloud St...

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IEEE International Conference on Utility and Cloud Computing (UCC)

作者： Ahcene Bounceur Saadat M. Alhashmi Foudil Mir Kara Mostefa College of Computing and Informatics University of Sharjah Sharjah UAE LIMED Laboratory Faculty of Exact Sciences University of Bejaia Bejaia Algeria Interdisciplinary Research Center for Intelligent Secure Systems KFUPM Dhahran KSA

ISBN: (数字)9798350367201

ISBN: (纸本)9798350367218

In a distributed environment where IoT devices collaborate on shared datasets, it is vital to establish a secure and efficient turn-taking process for data updates. Unlike centralized systems, where mutexes can effectively manage access to shared resources, distributed systems require alternative solutions. This is where distributed locks and leader election mechanisms are critical in maintaining order and consistency. The DoTRo (Dominating Tree Routing) Leader Election Algorithm stands out as a promising solution specifically designed for IoT applications, owing to its low power consumption. Remarkably, this algorithm achieves an impressive (85%) reduction in energy usage compared to traditional methods, making it highly efficient for resource-constrained environments. This paper explores the implementation of the DoTRo algorithm within the context of cloud storage, providing a detailed case study highlighting its effectiveness in managing data updates while minimizing energy consumption in distributed IoT settings. Through this examination, we aim to underscore the importance of innovative algorithms like DoTRo in optimizing performance and sustainability in future IoT applications.

关键词： Cloud computing Energy consumption Power demand Voting distributed databases Routing Energy efficiency Internet of Things Sustainable development distributed algorithms

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Graph Neural Network Based on Spectral Parameter Estimation for Mobile Networks

Graph Neural Network Based on Spectral Parameter Estimation ...

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International Conference on Engineering and Emerging Technologies (ICEET)

作者： Renhong Jin Xin Yan School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan China

ISBN: (数字)9798331532895

ISBN: (纸本)9798331532901

For online learning, Graph Neural Networks(GNNs) often require real graph data for parameter fine-tuning, but obtaining the graph data is challenging. Currently, GNNs are trained based on existing graph data. When learning in dynamic networks, spatial-domain GNNs use the adjacency matrix of entire graphs as its input, which are extremely resource-intensive in terms of computation and storage while dealing with large-scale graph data. Moreover, spectral-domain GNNs suffer from high spectral decomposition complexity. To enhance the generalization of GNN models and achieve lightweight GNN models, this paper proposes a lightweight GNN model based on spectral domain, SDGAT(Spectral-Domain Graph Attention Network). By combining spectral domain graph convolution and attention mechanism, SDGAT can effectively capture the global structure and local features of a graph, which helps to suppress noise in the graph and improve the robustness of the model. Furthermore, a distributed estimation algorithm for dynamic network spectral parameters is proposed, which significantly reduces the computational overhead when processing large-scale graph data. Finally, authors validate the effectiveness and accuracy of SDGAT through classification and regression tasks, and explore the feasibility of extending this model to other GNNs.

关键词： Attention mechanisms Computational modeling Heuristic algorithms Transfer learning Estimation distributed databases Graph neural networks Data models distributed algorithms Spectral analysis

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On the Linear Convergence Rate of the distributed Block Proximal Method

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IEEE CONTROL SYSTEMS LETTERS 2020年第3期4卷 779-784页

作者： Farina, Francesco Notarstefano, Giuseppe Univ Bologna Dept Elect Elect & Informat Engn I-40136 Bologna Italy

The recently developed distributed Block Proximal Method, for solving stochastic big-data convex optimization problems, is studied in this letter under the assumption of constant stepsizes and strongly convex (possibly non-smooth) local objective functions. This class of problems arises in many learning and classification problems in which, for example, strongly-convex regularizing functions are included in the objective function, the decision variable is extremely high dimensional, and large datasets are employed. The algorithm produces local estimates by means of block-wise updates and communication among the agents. The expected distance from the (global) optimum, in terms of cost value, is shown to decay linearly to a constant value which is proportional to the selected local stepsizes. A numerical example involving a classification problem corroborates the theoretical results.

关键词： Random variables Convergence Linear programming Optimization Convex functions distributed algorithms Europe Optimization algorithms machine learning network analysis and control

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