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

作者： Harald Räcke Stefan Schmid Radu Vintan TU Munich TU Berlin EPFL

ISBN: (数字)9798350383508

ISBN: (纸本)9798350383515

To meet stringent performance requirements, communication networks are becoming increasingly programmable and flexible, supporting fast and frequent adjustments. However, reconfiguring networks in a dependable and transiently consistent manner is known to be algorithmically challenging. This paper revisits the fundamental problem of how to update the routes in a network in a (transiently) loop-free manner, considering both the Strong Loop-Freedom (SLF) and the Relaxed Loop-Freedom (RLF) *** present two fast algorithms to solve the SLF and RLF problem variants exactly, to optimality. Our algorithms are based on a parameterized integer linear program which would be intractable to solve directly by a classic solver. Our main technical contribution is a lazy cycle breaking strategy which, by adding constraints lazily, improves performance dramatically, and outperforms the state-of-the-art exact algorithms by an order of magnitude on realistic medium-sized networks. We further explore approximate algorithms and show that while a relaxation approach is relatively slow, with a local search approach short update schedules can be found, outperforming the state-of-the-art *** the theoretical front, we also provide an approximation lower bound for the update time of the state-of-the-art algorithm in the literature. As a contribution to the research community, we made all our code and implementations publicly available.

关键词： Schedules Codes Heuristic algorithms approximation algorithms Search problems Linear programming Communication networks

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Spatially Distributed Multi-Period Optimal Power Flow with Battery Energy Storage Systems

Spatially Distributed Multi-Period Optimal Power Flow with B...

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Annual North-American Power Symposium

作者： Aryan Ritwajeet Jha Subho Paul Anamika Dubey School of Electrical Engineering & Computer Science Washington State University Pullman WA USA Department of Electrical Engineering Indian Institute of Technology (BHU) Varanasi Varanasi UP India

ISBN: (数字)9798331521035

ISBN: (纸本)9798331521042

The growing presence of battery-based distributed energy resources (DERs) in power distribution systems necessitates the development of multi-period optimal power flow (MPOPF) algorithms. Generally, an MPOPF problem is formulated as a mixed integer non-convex programming (MINCP) problem and solved in centralized manner. The centralized solutions for MPOPF problem, termed as MPCOPF, suffer from scalability challenges. A typical solution time for a medium-sized (~100 bus system) is in the order of $10^{3}$ to $10^{4}$ seconds; such solution time-scales are too slow for operational decision-making. This paper introduces a spatially distributed algorithm to solve MPOPF problems, termed MPDOPF, designed to address these shortcomings. Our method breaks down the centralized MPOPF problem into smaller sub-problems, which are solved in parallel. We achieve network-level optimality using the Equivalent Network approximation (ENApp) algorithm, where neighboring agents iteratively exchange boundary voltage and power flow variables until convergence. We analyze the performance of the proposed MPDOPF algorithm using the IEEE 123 bus test system, providing insights into the advantages of distributed MPOPF frameworks in terms of solution time compared to centralized approaches.

关键词： Energy resources Scalability Simulation Power distribution Voltage Programming approximation algorithms Distributed power generation North America Load flow

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Reservoir Computing Based on LED model for Signal Equalization in VLC-OFDM System

Reservoir Computing Based on LED model for Signal Equalizati...

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Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Yeping Huang Xiong Deng Zhinan Sun Yixian Dong Xihua Zou Wei Pan Lianshan Yan Center for Information Photonics and Communications Southwest Jiaotong University Chengdu China

ISBN: (数字)9798350379266

ISBN: (纸本)9798350379273

Visible Light Communication (VLC) is a promising technology for next-generation wireless communication, but signal distortion caused by device nonlinearity remains a challenge. However, traditional reservoir computing (RC) method is data-driven, which means its performance is directly influenced by the quality and quantity of the training dataset. In this paper, a model-driven RC method is proposed, which utilizes nonlinear LED model as the activation function for RC to improve the performance of VLC-OFDM system. The numerical simulation results show that the model-driven RC method significantly reduces the system bit error rate (BER) compared with the traditional RC equalization algorithm. Additionally, this algorithm can increase the system rate more than 25% while under the hard-decision forward error correction (HD-FEC) BER limited.

关键词： Computational modeling Bit error rate Nonlinear distortion Reservoir computing Light emitting diodes Numerical simulation approximation algorithms Numerical models Visible light communication Photonics

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Primal-dual approximation algorithms for Node-Weighted Steiner Forest on planar graphs

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INFORMATION AND COMPUTATION 2013年 222卷 293-306页

作者： Moldenhauer, Carsten EPFL SB MATH AA CH-1015 Lausanne Switzerland

NODE-WEIGHTED STEINER FOREST is the following problem: Given an undirected graph, a set of pairs of terminal vertices, a weight function on the vertices, find a minimum weight set of vertices that includes and connects each pair of terminals. We consider the restriction to planar graphs where the problem remains NP-complete. Demaine et al. showed that the generic primal-dual algorithm of Goemans and Williamson is a 6-approximation on planar graphs. We present (1) two different analyses to prove an approximation factor of 3, (2) show that our analysis is best possible for the chosen proof strategy, and (3) generalize this result to feedback problems on planar graphs. We give a simple proof for the first result using contraction techniques and following a standard proof strategy for the generic primal-dual algorithm. Given this proof strategy our analysis is best possible which implies that proving a better upper bound for this algorithm, if possible, would require different proof methods. Then, we give a reduction on planar graphs of FEEDBACK VERTEX SET to NODE-WEIGHTED STEINER TREE, and SUBSET FEEDBACK VERTEX SET to NODE-WEIGHTED STEINER FOREST. This generalizes our result to the feedback problems studied by Goemans and Williamson. For the opposite direction, we show how our constructions can be combined with the proof idea for the feedback problems to yield an alternative proof of the same approximation guarantee for NODE-WEIGHTED STEINER FOREST. (C) 2012 Elsevier Inc. All rights reserved.

关键词： Node-Weighted Steiner Forest Generalized Steiner Tree Vertex feedback set Primal-dual algorithm approximation algorithms Planar graphs

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Time-Reversal of Stochastic Maximum Principle

Time-Reversal of Stochastic Maximum Principle

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IEEE Conference on Decision and Control

作者： Amirhossein Taghvaei William E. Boeing Department of Aeronautics and Astronautics University of Washington Seattle

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Stochastic maximum principle (SMP) specifies a necessary condition for the solution of a stochastic optimal control problem. The condition involves a coupled system of forward and backward stochastic differential equations (FBSDE) for the state and the adjoint processes. Numerical solution of the FBSDE is challenging because the boundary condition of the adjoint process is specified at the terminal time, while the solution should be adaptable to the forward in time filtration of a Wiener process. In this paper, a “time-reversal” of the FBSDE system is proposed that involves integration with respect to a backward in time Wiener process. The time-reversal is used to propose an iterative Monte-Carlo procedure to solves the FBSDE system and its time-reversal simultaneously. The procedure involves approximating the Föllmer’s drift and solving a regression problem between the state and its adjoint at each time. The procedure is illustrated for the linear quadratic (LQ) optimal control problem with a numerical example.

关键词： Monte Carlo methods Filtration Switched mode power supplies Optimal control Differential equations approximation algorithms Boundary conditions Iterative algorithms

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On computing approximate Lewis weights

arXiv

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arXiv 2024年

作者： Apers, Simon Gribling, Sander Sidford, Aaron Université Paris Cité CNRS IRIF Paris France Tilburg University Netherlands Stanford University United States

In this note we provide and analyze a simple method that given an n × d matrix, outputs approximate p-Lewis weights, a natural measure of the importance of the rows with respect to the p norm, for p ≥ 2. More precisely, we provide a simple post-processing procedure that turns natural one-sided approximate p-Lewis weights into two-sided approximations. When combined with a simple one-sided approximation algorithm presented by Lee (PhD thesis, ‘16) this yields an algorithm for computing two-sided approximations of the p-Lewis weights of an n × d-matrix using poly(d, p) approximate leverage score computations. While efficient high-accuracy algorithms for approximating p-Lewis had been established previously by Fazel, Lee, Padmanabhan and Sidford (SODA ‘22), the simple structure and approximation tolerance of our algorithm may make it of use for different applications. © 2024, CC BY.

关键词： approximation algorithms

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S-Boxes with Optimal Strict Avalanche Criterion using Chaotic Map

S-Boxes with Optimal Strict Avalanche Criterion using Chaoti...

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International Conference on Integrated Circuits, Design, and Verification (ICDV)

作者： Phuc-Phan Duong Hieu Minh Nguyen Ba-Anh Dao Thai-Ha Tran Binh Kieu-Do-Nguyen Cong-Kha Pham Trong-Thuc Hoang University of Electro-Communications (UEC) Tokyo Japan Academy of Cryptography Techniques 141 Chien Thang Tan Trieu Thanh Tri Hanoi Vietnam

ISBN: (数字)9798350371864

ISBN: (纸本)9798350371871

Substitution boxes (S-Boxes) are essential for improving security in the modern block cipher. The main criteria to evaluate an S-Box include Nonlinearity (NL), Strict Avalanche Criterion (SAC), and Bit Independence Criterion (BIC). This paper introduces a novel approach to constructing S-Boxes with optimal SAC. The algorithm utilizes the SAC parameters of the S-Box and a newly developed chaotic map. The proposed S-Box achieved optimal values for both SAC and BIC-SAC in the cryptanalysis results, outperforming previously designed S-Boxes. Furthermore, other evaluation criteria such as Nonlinearity, Differential approximation Probability, and Linear approximation Probability are considered satisfactory security levels.

关键词： Integrated circuit synthesis Chaos Ciphers Linear approximation approximation algorithms Security Logistics

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Linearly Solvable General-Sum Markov Games

Linearly Solvable General-Sum Markov Games

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Annual Allerton Conference on Communication, Control, and Computing

作者： Braden C. Soper Caleb J. Miller Dan M. Merl Lawrence Livermore National Laboratory Center for Applied Scientific Computing Livermore CA USA

ISBN: (数字)9798331541033

ISBN: (纸本)9798331541040

Linearly solvable Markov decision processes (LSMDPs) are a special class of Markov decision processes (MDPs) in which the optimal value function under an exponential transformation satisfies a linear equation. This model was previously extended to a class of two-player, zero-sum Markov games in which the game's equilibrium value function can similarly be derived from a linear equation. In this work, a new class of linearly solvable n-player, general-sum Markov games is proposed. We show that games in this class have a unique Nash equilibrium, and the equilibrium value functions can be derived from a single system of linear equations. We demonstrate how to approximate discrete-state, discrete-action Markov games outside this class through an embedding process analogous to the way LSMDPs approximate standard MDPs. An off-policy reinforcement learning algorithm for general-sum Markov games, which we call Nash-Z learning, is presented. We empirically demonstrate that Nash-Z learning finds equilibrium policies with low regret and that it finds these solutions orders of magnitude faster than the classic Nash-Q learning algorithm.

关键词： Computational modeling Markov decision processes Games Reinforcement learning Gaussian processes approximation algorithms Nash equilibrium Mathematical models Function approximation Standards

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Large-scale fault recovery method of power communication network under typhoon disaster

Large-scale fault recovery method of power communication net...

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Information Technology,Big Data and Artificial Intelligence (ICIBA), International Conference on IEEE International Conference on

作者： Liyuan Chen Wangshu Sun Lin Chai State Grid Zhejiang Electric Power Co. Ltd. Pingyang District Power Supply Company State Grid Zhejiang Electric Power Company State Grid Zhejiang Electric Power Co. LTD. Information and Communication Branch

ISBN: (数字)9798350363609

ISBN: (纸本)9798350363616

The scale and structure of the power communication network are becoming larger and more complex, and large-scale natural disasters such as typhoons pose a serious threat to the modern power communication network, so it is particularly important to quickly restore the normal communication of each substation after the failure. In this paper, the wind field model model is carried out to model the typhoon, and the failure probability of the communication link is calculated according to the maximum wind speed radius of the typhoon and the distance of the communication link from the center of the typhoon. Secondly, with the goal of minimizing recovery resources, a mathematical model of rapid recovery algorithm is established. Thirdly, an approximation algorithm based on the cost-effectiveness of fault links is proposed to solve the mathematical model. Finally, combined with the specific network topology, the recovery resource consumption of different fault recovery methods under the same fault scale is analyzed, and the experimental results show that the proposed method consumes less recovery resources than other methods when recovering the same number of faults.

关键词： Costs Substations Tropical cyclones Disasters Wind speed Simulation Probability approximation algorithms Mathematical models Communication networks

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Integrated Circuit Image Feature Extraction Based on K-Means Clustering Combined with Harris

Integrated Circuit Image Feature Extraction Based on K-Means...

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Machine Learning and Computer Application (ICMLCA), International Conference on

作者： Qing Liu Yubo Zhou Huiling Li Kun Chen Limin Zhao Xiangbing Li Yuxiang Zhao Jinfang Yang Jinbing Zhang School of Electronic Information & Electrical Engineering Tianshui Normal University Tianshui China Engineering Research Center of Integrated Circuit Packaging and Testing Ministry of Education Tianshui China Tianshui Huatian Technology Co. Ltd Tianshui China

ISBN: (数字)9798331530334

ISBN: (纸本)9798331530341

To effectively extract corner point feature information from IC chip images, a technique of extracting corner point feature information from IC defective chip images combining K-means clustering algorithm and Harris algorithm is proposed. Firstly, the traditional Harris algorithm is improved from the perspective of adapting to the processing of IC chip images; secondly, the IC chip images are detected using Harris corner point detection and then combined with K-means based clustering algorithm to achieve the optimal detection effect of the image target; finally, the proposed algorithm is compared with Moravec algorithm, ORB algorithm, SIFT algorithm and Finally, the proposed algorithm is compared with Moravec, ORB, SIFT and traditional Harris corner detection algorithms, and the performance of the algorithm is further explained by objective evaluation using direct statistics and common evaluation indexes such as the running time of the algorithm. The experimental results show that this method can achieve the corner point feature detection of IC chips, so that the obtained feature areas not only contain as many stable corner points as possible, but also do not overlap each other, and the method can effectively extract the real corner points in the image, which has strong applicability.

关键词： Integrated circuits Feature detection Clustering algorithms Machine learning Feature extraction approximation algorithms Production facilities Data mining Indexes Surface treatment

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