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22nd IEEE International Symposium on Parallel and Distributed Processing with Applications, ISPA 2024

作者： Peng, Tianwen Chen, Long Huang, Jiale Wu, Jigang Guangdong University of Technology School of Computer Science and Technology Guangzhou510006 China

ISBN: (纸本)9798331509712

The energy consumption of edge devices or nodes is critical to ensure a long lifetime of cooperative edge-AI service network, which has been somehow overlooked in the literature. Failure to accommodating the energy depletion can not only bring quality of service degradation of mobile terminal devices, but can also harm the connectivity of the multi-access edge computing network. This paper thus addresses the application service fairness problem under energy depletion constraints, to make the service fairness paradigm practical to suit for energy-limited edge nodes, e.g., the unmanned areal vehicles (UAVs), solar energy powered road side units (RSUs). The problem is formulated as a non-convex integer linear programming, which is NP-hard. Then a randomized rounding algorithm as well as a greedy algorithm are designed to maximize the minimum service type's completion rate. Extensive simulation results have shown that compared to the algorithms without energy constraints, the proposed randomized rounding algorithm and greedy algorithm with energy constraints can reduce the average energy consumption by about 39.87% and 40.31% respectively, at the cost of a mild average system throughput degradation. © 2024 IEEE.

关键词： integer linear programming

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An Optimization Approach to Current State Opacity Assessment 63

An Optimization Approach to Current State Opacity Assessment

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Basile, Francesco De Tommasi, Gianmaria Dubbioso, Sara Fiorenza, Federico University of Salerno Diem Fisciano84084 Italy Università Degli Studi di Napoli Federico Ii Dieti Via Claudio 21 Napoli80125 Italy

ISBN: (纸本)9798350316339

This paper provides a necessary and sufficient condition to assess Current State Opacity (CSO) in discrete event systems modeled as bounded Petri nets. The provided condition requires to check opacity on a finite number of sequences. By exploiting the algebraic representation of Petri nets, we show how to turn the required checks into the solution of an optimization problem. Therefore, the proposed approach enables to perform CSO assessment by using off-the-shelf commercial software, without the need to build any observer, neither complete nor reduced, hence being less affected by the curse of dimensionality. © 2024 IEEE.

关键词： integer linear programming

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Optimal Network Reconfiguration for Mitigating the Impact of Adverse Weather Events on Distribution Networks 7

Optimal Network Reconfiguration for Mitigating the Impact of...

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7th IEEE International Humanitarian Technologies Conference, IHTC 2024

作者： Velini, Angelo Cometa, Roberto Lorusso, Francesco La Scala, Massimo Bruno, Sergio DEI - Politecnico di Bari Bari Italy

ISBN: (纸本)9798350354645

Adverse weather events can have disastrous effects on power system infrastructure, hampering the reliable and secure operation of substations and underground cables in case of flooding and heat waves, overhead lines, towers and pole-mount transformers in case of high-speed wind gusts. This paper investigates the impact of adverse weather events on the primary distribution networks reliability, in terms of components failure and repair rates. Since the power supply quality indices commonly used for a reliability assessment depend on these parameters, more suitable topological assets can be found considering the influence of adverse weather conditions. The effects of meteorological events are observed on the reconfigured topologies obtained from an Optimal Network Reconfiguration algorithm based on mixed-integer linear programming applied to a realistic sized distribution network. © 2024 IEEE.

关键词： integer linear programming

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Comprehensive Evaluation of Distribution Network Planning Based on Super Efficiency Data Envelopment Analysis Algorithm 2

Comprehensive Evaluation of Distribution Network Planning Ba...

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2nd IEEE International Conference on Data Science and Network Security, ICDSNS 2024

作者： Liang, Hao Guo, Yue Liu, Yanru State Grid Corporation of China Beijing China State Grid Economic and Technological Research Institute Co. Ltd Beijing China

ISBN: (纸本)9798350373110

The primary goal of evaluating the Distribution Network Planning (DNP) is to design systems that can meet growing demand in a cost-effective, and reliable network operations. The proposed research focused on improving the Data Envelopment Analysis (DEA) as a Super Efficiency DEA (SE-DEA) for comprehensive evaluation of the DNP. Initially, the evaluation parameters of DEA such as fuzzy number aggregation and investment efficiency are evaluated and analysed. To strengthen the evaluation of DNP planning, the traditional DEA model is improved by decomposing each Decision Making Unit (DMU) into sub system DMUs, considering the dynamic nature of multi-period evaluations. The SE-DEA model is then evaluated for measuring the efficiency of the DNP model. The Malmquist Productivity Index (MPI) is used to evaluate the level of productivity growth in the long-term period. The experimental simulation of the proposed SE-DEA-DNP showed effective Comprehensive Efficiency Value (CEV) of 0.83 and Evaluation Value (EV) of 1.72 which are superior when compared to the traditional methods Active Distribution Networks with Mixed integer linear programming (ADNs-MILP) and ADN-linear Decision Rules (ADN-LDR). © 2024 IEEE.

关键词： integer linear programming

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A GRAPHICAL SOFTWARE TOOL WITH integer linear programming FOR MICROCONTROLLER INPUT/OUTPUT INTERFACE SELECTION FEASIBILITY

A GRAPHICAL SOFTWARE TOOL WITH INTEGER LINEAR PROGRAMMING FO...

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26th IEEE Annual Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： Manjikian, Naraig Ferdynus, Alexander Katona, Laszlo Queens Univ Dept Elect & Comp Engn Kingston ON K7L 3N6 Canada Aztech Associates Inc Kingston ON Canada

ISBN: (纸本)9781479900336;9781479900312

This paper describes a graphical and interactive software tool to support embedded systems engineering with highly integrated microcontrollers such as the ColdFire MCF54418. Such products have many input/output interfaces that share chip pins, hence not all possible combinations of active interfaces are feasible due to pin conflicts. To address challenges stemming from such conflicts, the software tool described in this paper provides early decision support for selection and subsequent hardware configuration of interfaces. An XML input file describes pins and interfaces of a microcontroller. From this information, the software tool generates an interactive graphical representation for a designer to interactively explore interfaces and pins, to visualize interface conflicts due to shared pins, and to incrementally develop conflict-free interface combinations. More importantly, the tool provides higher-level automated decision support with integer linear programming to solve an optimization problem and conclusively determine whether there exists a feasible conflict-free selection for given specifications on desired types and numbers of interfaces. Finally, for general-purpose input/output, the tool also has a more specialized mode that enables a user to indicate application-specific grouping and direction of pins. From this information, the tool automatically tailors an application programming interface in C code.

关键词： Embedded systems microcontrollers integer linear programming

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Satellite Communications Resilience - Service Restoration and Retainment

Satellite Communications Resilience - Service Restoration an...

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41st IEEE Military Communications Conference (IEEE MILCOM) - Communications Supporting Military Operations in a Contested Environment

作者： Gobbi, Richard L. Schaefer, Elsa Jacobs, Jabril Street, Dow LinQuest Corp Chesapeake VA 23320 USA LinQuest Corp Herndon VA USA LinQuest Corp Los Angeles CA USA LinQuest Corp San Francisco CA USA

ISBN: (纸本)9798350321814

A network modeling and resilience quantification approach is described for multiple-beam, geosynchronous-orbit satellite communications (SATCOM) systems operating in the millimeter wave (similar to 20-300 GHz) spectral region providing frequency reuse and dual polarization coverage of user terminals (UTs) and gateways. Focus is on the UT service restoration process in face of jamming attacks on multiple beams, including the retainment of service to collaterally affected UTs. The combinatorial optimization approach used to determine alternative pointing of UTs to beams on the attacked satellite, or to beams on satellites in adjacent orbital slots, is a Multiple Knapsack Problem (MKP) formulation. The cascading effect of jamming attacks on connected UTs removed by one or more satellite hops from jammed UTs is addressed and related to the graph theoretical component structure of the UT network;this forms an analytical basis for addressing overall network disruption due to jamming attacks. The MKP formulation is extended to include the case of multiple service provider ( SP) sharing of the satellite spectrum, enabling assessment of the effect on competitive SPs due to cooperation in the form of the sharing of beam capacity. The MKP is solved using a constraint programming (CP) technique which allows latitude in the choice of objective functions.

关键词： Resilience SATCOM resilience Satellite system threats integer linear programming Multiple knapsack problems Constraint programming Graph theory and SATCOM systems

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Intelligent reflecting surface-aided network planning

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IET COMMUNICATIONS 2022年第20期16卷 2406-2413页

作者： Tseng, Fan-Hsun Liang, Yu-Shan Ti, Yen-Wu Yu, Chia-Mu Natl Cheng Kung Univ Dept Comp Sci & Informat Engn Tainan Taiwan Natl Kaohsiung Univ Sci & Technol Dept Elect Engn Kaohsiung Taiwan Yango Univ Coll Artificial Intelligence Fuzhou Peoples R China Natl Yang Ming Chiao Tung Univ Dept Informat Management & Finance Hsinchu Taiwan

Intelligent reflecting surface (IRS) composed of a large number of low-cost, phase-adjustable passive reflecting elements, which is an attractive solution of overcoming the signal attenuation and interference. IRS can be used as a low-power passive system with signal enhancement and interference suppression. However, the planning problem of a large-scale network contains a great numbers of base stations (BSs) and IRSs is challenging. The network planning problem considers limited deployment cost and signal enhancement at the same time is vital. Here, the 6G wireless signal coverage (WSC) problem with the consideration of both BS and IRS is considered. More specifically, the 6G WSC problem is first formulated through the integer linear programming. Due to its obvious NP-hardness, two efficient heuristic algorithms that can reach a near-optimal solution, that is, the WSC algorithm and the tree-based WSC (TBWSC) algorithm is then proposed. Simulation-based results showed that the proposed WSC algorithm achieves lower total cost than that of the TBWSC algorithm but also results in lower signal quality. The proposed TBWSC algorithm obtains the planning result with the highest signal quality and slightly higher total cost. Both proposed algorithms can find better planning results of multiple BSs and IRSs for 6G wireless communications.

关键词： near-optimal solution 6G WSC problem network planning problem 6G mobile communication integer linear programming NP-hard problem TBWSC intelligent materials telecommunication power management tree-based WSC algorithm TBWSC algorithm IRS computational complexity efficient heuristic algorithms telecommunication network planning 6G wireless signal coverage problem linear programming low-power passive system signal enhancement interference suppression large-scale network integer programming signal attenuation radiofrequency interference limited deployment cost phase-adjustable passive reflecting elements trees (mathematics) intelligent reflecting surface

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XEngine: Optimal Tensor Rematerialization for Neural Networks in Heterogeneous Environments

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ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION 2022年第1期20卷 1-25页

作者： Schuler, Manuela Membarth, Richard Slusallek, Philipp Deutsch Forschungszentrum Kunstl Intelligenz DFKI Saarland Informat Campus D-66123 Saarbrucken Germany TH Ingolstadt Res Inst Almot Bavaria D-85049 Ingolstadt Germany Saarland Univ Saarland Informat Campus D-66123 Saarbrucken Germany

Memory efficiency is crucial in training deep learning networks on resource-restricted devices. During backpropagation, forward tensors are used to calculate gradients. Despite the option of keeping those dependencies in memory until they are reused in backpropagation, some forward tensors can be discarded and recomputed later from saved tensors, so-called checkpoints. This allows, in particular, for resource-constrained heterogeneous environments to make use of all available compute devices. Unfortunately, the definition of these checkpoints is a non-trivial problem and poses a challenge to the programmer-improper or excessive recomputations negate the benefit of checkpointing. In this article, we present XEngine, an approach that schedules network operators to heterogeneous devices in low memory environments by determining checkpoints and recomputations of tensors. Our approach selects suitable resources per timestep and operator and optimizes the end-to-end time for neural networks taking the memory limitation of each device into account. For this, we formulate a mixed-integer quadratic program (MIQP) to schedule operators of deep learning networks on heterogeneous systems. We compare our MIQP solver XEngine against Checkmate [12], a mixed-integer linear programming (MILP) approach that solves recomputation on a single device. Our solver finds solutions that are up to 22.5% faster than the fastest Checkmate schedule in which the network is computed exclusively on a single device. We also find valid schedules for networks making use of both central processing units and graphics processing units if memory limitations do not allow scheduling exclusively to the graphics processing unit.

关键词： Rematerialization integer linear programming neural networks memory management heterogeneous computing

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Checking Phylogenetics Decisiveness in Theory and in Practice

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2022年第6期19卷 3307-3316页

作者： Parvini, Ghazaleh Braught, Katherine Fernandez-Baca, David Univ Massachusetts Coll Informat & Comp Sci Amherst MA 01003 USA Univ Illinois Dept Comp Sci Urbana IL 61801 USA Iowa State Univ Dept Comp Sci Ames IA 50011 USA

Suppose we aim to build a phylogeny for a set of taxa X using information from a collection of loci, where each locus offers information for only a fraction of the taxa. The question is whether, based solely on the pattern of data availability, called a taxon coverage pattern, one can determine if the data suffices to construct a reliable phylogeny. The problem can be expressed combinatorially as follows. Let us call a taxon coverage pattern decisive if, for any binary phylogenetic tree T for X, the collection of phylogenetic trees obtained by restricting T to the subset of X covered by each locus uniquely determines T. Here we relate the problem of checking whether a taxon coverage pattern is decisive to a hypergraph coloring problem. Using this connection, we (1) show that checking decisiveness is co-NP complete;(2) obtain lower bounds on the amount of coverage needed to achieve decisiveness;(3) devise an exact algorithm for decisiveness;(4) develop problem reduction rules, and use them to obtain efficient algorithms for inputs with few loci;and (5) devise Boolean satisfiability (SAT) and integer linear programming formulations (ILP) of decisiveness that allow us to analyze data sets that arise in practice. For data sets that are not decisive, we use our SATand ILP formulations to obtain decisive subsets of the data.

关键词： Phylogeny Partitioning algorithms Color Terminology Steel Software Reliability Phylogenetic tree taxon coverage algorithms no-rainbow hypergraph coloring integer linear programming satisfiability

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Collaborative passenger flow control for oversaturated metro lines: a stochastic optimization method

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TRANSPORTMETRICA A-TRANSPORT SCIENCE 2022年第3期18卷 619-658页

作者： Meng, Fanting Yang, Lixing Shi, Jungang Jiang, Zhong-Zhong Gao, Ziyou Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing Peoples R China East China Jiaotong Univ Coll Transportat & Logist Nanchang Jiangxi Peoples R China Tongji Univ Shanghai Key Lab Rail Infrastruct Durabil & Syst Shanghai Peoples R China Northeastern Univ Sch Business Adm Shenyang Peoples R China Northeastern Univ Inst Behav & Serv Operat Management Shenyang Peoples R China

With the rapid increase in travel demands in urban areas, large passenger flow becomes a common phenomenon in the metro system of some large cities. To ensure the safety and improve the operational efficiency of the metro system, this paper proposes an effective method to formulate a robust passenger flow control strategy over a metro line, in which the stochastic and dynamic passenger flow is specifically considered. By discretizing the time horizon into a series of time intervals, we propose an integer linear programming model aimed at minimizing the expected passenger waiting time over the metro line. To solve the proposed model, a heuristic algorithm that integrates the Lagrangian relaxation approach and CPLEX solver is designed to search for high-quality solutions for the problem of interest. Finally, two sets of numerical experiments, including a small-scale case and a real-world instance, are implemented to validate the performance of the proposed approaches.

关键词： Passenger flow control stochastic and dynamic passenger demand integer linear programming Lagrangian relaxation

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