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IEEE Conference on Global Communications (IEEE GLOBECOM) - Intelligent Communications for Shared Prosperity

作者： Sato, Takehiro Kurimoto, Takashi Urushidani, Shigeo Oki, Eiji Kyoto Univ Kyoto Japan Natl Inst Informat Tokyo Japan

ISBN: (纸本)9798350310900

This paper proposes a scheduling model for updating resource allocations for virtualized networks (VNs) without congestion. The proposed model determines the schedule of migrating traffic flows on VNs from old routes to new routes. The model aims to minimize the number of rounds required to complete the update of all existing VNs. We evaluate the performance of model in terms of the percentage of trials where feasible update scheduling exists and the number of rounds required to complete the update. Numerical results show that more rounds are required to achieve congestion-free update when the traffic demand or the number of VNs increases. The number of required rounds tends to remain the same when the maximum number of rounds exceeds a certain value;this observation helps network operators estimate the time required for VN update.

关键词： Network virtualization optimization model integer linear programming network update

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Multiple Constant Multiplication: From Target Constants to Optimized Pipelined Adder Graphs 33

Multiple Constant Multiplication: From Target Constants to O...

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33rd International Conference on Field-Programmable Logic and Applications (FPL)

作者： Remi, Garcia Anastasia, Volkova Nantes Univ Ecole Cent Nantes CNRS LS2NUMR 6004 F-44000 Nantes France

ISBN: (纸本)9798350341515

Multiple Constant Multiplication (MCM) is a ubiquitous problem for numerous computation-intensive applications. One efficient approach is to replace generic multipliers by multiplierless architectures based on bit-shifts and additions. The adder graphs describing the multiplierless circuits can be optimized according to various metrics. In this paper, we optimize for throughput and improve the state-of-the-art for the design of pipelined adder graphs. In contrast to existing approaches, which pipeline a posteriori or use heuristics, our solution is to optimally solve the pipelined adder graph design problem using Mixed-integer linear programming (MILP). We first model the pipelining and its cost, and then incorporate it into the state-of-the-art ILP model for the MCM design. Fusing the MCM design with pipelining into a single global optimization problem exactly solved by powerful MILP solvers demonstrated clear benefits on numerous benchmarks. Moreover, mathematical modeling allows for an easily extendable tool which can adapt to evolving hardware models/metrics.

关键词： Adder graph optimal design multiplierless hardware integer linear programming

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Dynamic parking space allocation at urban scale: Problem formulation and resolution

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JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES 2022年第10期34卷 9576-9590页

作者： Errousso, Hanae El Ouadi, Jihane Alaoui, El Arbi Abdellaoui Benhadou, Siham Res Fdn Dev & Innovat Sci & Engn Casablanca 8118 Morocco HASSAN II Univ Natl & High Sch Elect & Mech Casablanca 8118 Morocco EIGSI Casablanca 20410 Morocco Moulay Ismail Univ Ecole Normale Super Meknes 3104 Morocco

Searching for an available parking space is a major cause of traffic congestion and pollution. Besides, getting a free spot constitutes a primary worry for drivers on the road, which results in their daily discomfort and stress. Therefore, well-designed parking management tools are needed to effectively allocate parking spaces to drivers, especially in dense urban areas. In this perspective, we propose two linear integer programming models for assigning parking spaces to all road users (private vehicles and carriers) while maximizing parking occupancy. The first combinatorial problem attributes to each driver only one parking space while the second one assigns two parking spaces if no space is suitable for that motorist. Feasible solutions are computed in an exact way by improved primal simplex method and in an approximated manner by two metaheuristics (Genetic algorithm and Taboo search) for larger scale applications. However, parking problems still persist when parking requests are not properly balanced between a city's zones, a local gridlock problem arises where certain areas are over-used and others under-used. For this reason, we first redistribute parking demands over urban areas before dedicating one or two spaces to each driver. To do this, we consider both solicitation rates in these areas and coverage ratios of received parking demands. Our parking space allocation solution is just one component of a transportation system heavily backed by information and communication technologies. This system consists of effectively managing a city's parking spaces by predicting and understanding their occupancy patterns. The suggested approach is applied to Casablanca city with several parking scenarios in order to evaluate its effectiveness and test its ability to minimize total walking distance, parking costs as well as unmet demand percentages. Experimental results show that our mathematical models can effectively rule out parking problems. The related published met

关键词： Freight transport Smart system Parking space allocation integer linear programming Combinatorial problem Optimization algorithms

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FAST EVALUATION OF GENERALIZED TODD POLYNOMIALS: APPLICATIONS TO MACMAHON’S PARTITION ANALYSIS AND integer programming

arXiv

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arXiv 2023年

作者： Xin, Guoce Zhang, Yingrui Zhang, Zihao School of Mathematical Sciences Capital Normal University Beijing100048 China KLMM Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

The Todd polynomials, denoted as tdk(b1, b2, . . ., bm), are characterised by their generating functions: (formula presented) These polynomials serve as fundamental components in the Todd class of toric varieties, a concept of significant relevance in the study of lattice polytopes and number theory. We identify that generalised Todd polynomials emerge naturally within the framework of MacMahon’s partition analysis, particularly in the context of computing Ehrhart series. We introduce an efficient method for the evaluation of generalised Todd polynomials for numerical values of bi. This is achieved through the development of expedited operations in the quotient ring Zp[[s]] modulo sd, where p is a large prime. The practical implications of our work are demonstrated through two applications: firstly, we facilitate a recalculated resolution of the Ehrhart series for magic squares of order 6, a problem initially addressed by the first author, reducing computation time from 70 days to approximately 1 day;secondly, we present a polynomial-time algorithm for integer linear programming when the dimension is fixed, exhibiting a notable enhancement in computational *** Codes Primary 05-04, Secondary 05E14, 05A15 Copyright © 2023, The Authors. All rights reserved.

关键词： integer linear programming

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Collaborative Data Offloading for Earth Observation Satellite Networks

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IEEE COMMUNICATIONS LETTERS 2022年第5期26卷 1116-1120页

作者： He, Lijun Guo, Kun Gan, Hongping Wang, Li Northwestern Polytech Univ Sch Software Xian 710072 Shaanxi Peoples R China NPU Yangtze River Delta Res Inst Taicang 215400 Jiangsu Peoples R China East China Normal Univ Sch Commun & Elect Engn Shanghai 200241 Peoples R China

We study the collaborative data offloading problem for earth observation satellite networks (EOSNs) that allows light-loaded satellites to assist heavily-loaded ones to offload earth observation data. First, we propose a task flow graph (TFG) to depict the collaborative data offloading procedure. Based on the proposed TFG, we formulate the studied problem as integer linear programming (ILP) to maximize the weighted sum of successfully offloaded tasks. Then, we leverage the underlying structure of ILP to propose a fast yet efficient algorithm. Finally, our simulation results demonstrate that collaborative data offloading can significantly improve the performance of the EOSNs.

关键词： Task analysis Satellites Collaboration Earth Data models Satellite antennas Windows Collaborative data offloading task flow graph integer linear programming

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A Strong Separation for Adversarially Robust 0 Estimation for linear Sketches 65

A Strong Separation for Adversarially Robust 0 Estimation fo...

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65th IEEE Annual Symposium on Foundations of Computer Science, FOCS 2024

作者： Gribelyuk, Elena Lin, Honghao Woodruff, David P. Yu, Huacheng Zhou, Samson Princeton University Department of Computer Science PrincetonNJ United States Carnegie Mellon University Computer Science Department PittsburghPA United States Texas A and M University Department of Computer Science College StationTX United States

ISBN: (纸本)9798331516741

The majority of streaming problems are defined and analyzed in a static setting, where the data stream is any worst-case sequence of insertions and deletions which is fixed in advance. However, many real-world applications require a more flexible model, where an adaptive adversary may select future stream elements after observing the previous outputs of the algorithm. Over the last few years, there has been increased interest in proving lower bounds for natural problems in the adaptive streaming model. In this work, we give the first known adaptive attack against linear sketches for the well-studied 0-estimation problem over turnstile, integer streams. For any linear streaming algorithm A which uses sketching matrix Aϵ Zr×n, this attack makes Õ(r8) queries and succeeds with high constant probability in breaking the sketch. Additionally, we give an adaptive attack against linear sketches for the 0-estimation problem over finite fields Fp, which requires a smaller number of Õ(r3) queries. Finally, we provide an adaptive attack over {Rn against linear sketches A in Rr×n for 0-estimation, in the setting where A has all nonzero subdeterminants at least 1poly(r). Our results provide an exponential improvement over the previous number of queries known to break an 0-estimation sketch. © 2024 IEEE.

关键词： integer linear programming

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Win-Win: On Simultaneous Clustering and Imputing over Incomplete Data 50th

Win-Win: On Simultaneous Clustering and Imputing over Incomp...

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50th International Conference on Very Large Data Bases, VLDB 2024

作者： Sun, Yu Zhu, Jingyu Xu, Xiao Xu, Xian Sun, Yuyao Song, Shaoxu Li, Xiang Yuan, Xiaojie College of Computer Science Nankai University China Nankai University China Ant Group China Tsinghua University China Ping An Health Technology China

Although clustering methods have shown promising performance in various applications, they cannot effectively handle incomplete data. Existing studies often impute missing values first before clustering analysis and conduct these two processes separately. How ever, inaccurate imputation does not necessarily contribute positively to the subsequent clustering. Intuitively, accurate imputation and clustering can serve and benefit from each other, where clustering-based imputation methods typically utilize cluster signals to impute incomplete data and accurate fillings are expected to bring more valuable data for clustering. Therefore, in this manuscript, rather than considering two tasks independently or con ducting them respectively, we study simultaneous clustering and imputing over incomplete data. The immediate benefit is that such a strategy improves both clustering and imputation performance simultaneously, to get a win-win result. Our major technical high lights include (1) the problem formalization and NP-hardness analysis on computing simultaneous clustering and imputing results, (2) exact solutions by transforming the problem as the integer linear programming (ILP) formulation, and (3) efficient approximation algorithms based on the linear programming (LP) relaxation and local neighbors (LN) solution, with approximation guarantees. Experiments on various real-world datasets demonstrate the superiority of our work in clustering and imputing incomplete data. © 2024, VLDB Endowment. All rights reserved.

关键词： integer linear programming

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Graphic Approximation of integer Sequences 1

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53rd Southeastern International Conference on Combinatorics, Graph Theory, and Computing, SEICCGTC 2022

作者： Cloteaux, Brian National Institute of Standards and Technology Applied and Computational Mathematics Division GaithersburgMD United States

ISBN: (数字)9783031621666

ISBN: (纸本)9783031621659

A variety of network modeling problems begin by generating a degree sequence drawn from a given probability distribution. If the randomly generated sequence is not graphic, we give two new approaches for generating a graphic approximation of the sequence. These schemes are fast, simple to implement, and only require a linear amount of memory. This allows approximation to be performed on very large integer sequences. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： integer linear programming

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PACE Solver Description: UzL Exact Solver for One-Sided Crossing Minimization 19

PACE Solver Description: UzL Exact Solver for One-Sided Cros...

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19th International Symposium on Parameterized and Exact Computation, IPEC 2024

作者： Bannach, Max Chudigiewitsch, Florian Klein, Kim-Manuel Wienöbst, Marcel European Space Agency Noordwijk Netherlands Institute for Theoretical Computer Science University of Lübeck Germany

ISBN: (纸本)9783959773539

This document contains a short description of our solver pingpong for the one-sided crossing minimization problem that we submitted to the exact and parameterized track of the PACE challenge 2024. The solver is based on the well-known reduction to the weighted directed feedback arc set problem. This problem is tackled by an implicit hitting set formulation using an integer linear programming solver. Adding hitting set constraints is done iteratively by computing heuristic solutions to the current formulation and finding cycles that are not yet "hit." The procedure terminates if the exact hitting set solution covers all cycles. Thus, optimality of our solver is guaranteed. © Max Bannach, Florian Chudigiewitsch, Kim-Manuel Klein, and Marcel Wienöbst.

关键词： integer linear programming

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A Multi-task Assignment Algorithm for UAV Cluster Collaborative Emergence Based on Iterative MILP

A Multi-task Assignment Algorithm for UAV Cluster Collaborat...

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2024 Jiangsu Annual Conference on Automation, JACA 2024

作者： Wang, Ning Guo, Xiang-Gui Liu, Xiong-Jun Yue, Tian-Yu Beijing Jinghang Computation and Communication Research Institute Beijing100005 China Beijing Engineering Research Center of Industrial Spectrum Imaging School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Shunde Innovation School University of Science and Technology Beijing Foshan528000 China

ISBN: (纸本)9781837242689

In this paper, an iterative mixed integer linear programming (MILP) algorithm based on the traditional MILP algorithm is proposed to realize the multi-task assignment oi unmanned aerial vehicle (UAV) cluster collaborative emergence. This algorithm uses iteration and prediction method to avoid the delect oi traditional MILP algorithm that requires scene update to carry out the next calculation, and by using the current task assignment result to carry out the next prediction, the information utilization degree is improved, and the real-time performance is greatly improved. Finally, simulation results show that the proposed iterative MILP algorithm has better real-time and collaborative emergence characteristics than the traditional MILP algorithm. © The Institution of Engineering & Technology 2024.

关键词： integer linear programming

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