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An Architecture and a MAC Protocol for Throughput Improvement in Light Trail Networks

IEICE TRANSACTIONS ON COMMUNICATIONS 2012年第7期E95B卷 2330-2343页

作者： Chen, Wenjie Fukushima, Yukinobu Yokohira, Tokumi Okayama Univ Grad Sch Nat Sci & Technol Okayama 7008530 Japan

Light trail architecture is attracting attention as a new optical wavelength-division multiplexing network architecture that can be built with currently available devices and can achieve bandwidth allocation with granularity finer than a wavelength. Because a light trail is a shared medium, we need a medium access control (MAC) protocol to prevent collisions. Although MAC protocols using token passing can prevent collisions, the bandwidths of links that are located upstream of the token holding node are kept idle. We first propose a dynamic light trail splitting method for increasing throughput of a light trail by using such idle bandwidths. Our method splits a trail into upstream and downstream trails at the token holding node, and independent data transmission on the two trails are permitted. As a result, we expect that the split trail architecture will achieve higher throughput than the original non-split trail architecture. The degree of performance improvement with the split trail architecture depends on how appropriately we determine the upstream and downstream token holding times of every transmission node. Thus, we formulate a problem in which we optimize the token holding times to accommodate requested traffic volume as a linear programming problem. We then derive the throughput of the split trail architecture by solving the problem using the NUOPT solver and investigate the degree of improvement over the original architecture. In addition, we evaluate the end-to-end delay of the split trail architecture by simulation. According to numerical examples, the split trail architecture achieves 1) almost the same throughput as the original one for the worst-case traffic pattern where every transmission node sends data to the terminating node of the trail only, 2) about 1.6 times higher throughput for a uniform traffic pattern where every node pair requests the same traffic volume and an extremely unbalanced traffic pattern where only a few node pairs request huge

关键词： light trail network medium access control (MAC) token passing linear programming problem

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Recursive Algorithm for L1 Norm Estimation in linear Models

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JOURNAL OF SURVEYING ENGINEERING 2011年第1期137卷 1-8页

作者： Khodabandeh, A. Amiri-Simkooei, A. R. Univ Tehran Dept Surveying & Geomat Engn Geodesy Div Fac Engn Tehran Iran Delft Univ Technol Delft Inst Earth Observat & Space Syst Fac Aerosp Engn NL-2629 HS Delft Netherlands Univ Isfahan Dept Surveying Engn Fac Engn Esfahan 81744 Iran

L1 norm estimator has been widely used as a robust parameter estimation method for outlier detection. Different algorithms have been applied for L1 norm minimization among which the linear programming problem based on the simplex method is well known. In the present contribution, in order to solve an L1 norm minimization problem in a linear model, an interior point algorithm is developed which is based on Dikin's method. The method can be considered as an appropriate alternative for the classical simplex method, which is sometimes time-consuming. The proposed method, compared with the simplex method, is thus easier for implementation and faster in performance. Furthermore, a recursive form of the Dikin's method is derived, which resembles the recursive least-squares method. Two simulated numerical examples show that the proposed algorithm gives as accurate results as the simplex method but in considerably less time. When dealing with a large number of observations, this algorithm can thus be used instead of the iteratively reweighted least-squares method and the simplex method.

关键词： Iteratively reweighted least squares linear programming problem Interior point methods Simplex method Affine method of Dikin Robust estimation L1 norm minimization Recursive algorithm

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A linear programming approach towards individuation lighting system with optimal energy consumption

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Materials Today: Proceedings 2019年 17卷 168-175页

作者： Chevikala Divya Namratha Pai Department of Electrical and Electronics Engineering MIT Manipal Academy of Higher Education Manipal 576104 India

Energy consumption is considered to be scope for wide range of research. This paper is an attempt to the process of energy conservation in the field of lighting science. A classroom with multiple locations and different combinations of four luminaires were considered for the study. linear programming problem is used to optimize the energy consumption with respect to illuminance at particular location. This study depicts the relation between energy consumption and number of luminaires at certain location considering individual satisfaction as a dynamic factor. Result shows the effectiveness of the methodology on light energy consumption satisfying individual preferred illuminance.

关键词： linear programming problem Energy conservation Individual preferred illuminance

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-gain control on positive impulsive system via a hybrid proportional plus integral algorithm

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IET Control Theory & Applications 2019年第7期13卷 898-904页

作者： Hao Chen Tao Zhan Qinzhen Huang College of Electrical and Information Engineering Southwest Minzu University Chengdu 610041 People's Republic of China Department of Applied Mathematics University of Waterloo Waterloo Ontario N2L 3G1 Canada School of Mathematics Shandong University Jinan Shandong 250100 People's Republic of China

In this study, the -gain control issues on positive system are investigated. A hybrid proportional impulsive with integral (PII) control scheme is proposed. This impulse-time-dependent control algorithm uses the proportional control action at impulse instants for stabilising, and applies the integral control strategy between impulse time intervals for improving the state convergence, respectively. The average impulsive interval approach and co-positive Lyapunov function method are employed to derive the sufficient conditions. Then -gain performance of the impulsive positive system can be guaranteed by solving the linear programming problem. In addition, iterative convex optimisation algorithm is presented for the design of PII control gain matrices. Numerical examples illustrate the expected results of this design.

关键词： Lyapunov methods matrix algebra gain control control system synthesis linear programming time-varying systems iterative methods convex programming stability impulse time intervals co-positive Lyapunov function method impulsive positive system iterative convex optimisation algorithm PII control gain matrices positive impulsive system hybrid proportional plus integral algorithm integral control scheme impulse-time-dependent control algorithm impulse instants impulsive interval approach integral control strategy 𝒦1 stability proportional control action Kp ℒ1 -gain control issues linear programming problem

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Real time scheduler for multiprocessor systems based on continuous control using Timed Continuous Petri Nets ⁎

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IFAC-PapersOnLine 2020年第4期53卷 371-377页

作者： L. Rubio-Anguiano A. Ramírez-Treviño A. Chils J.L. Briz CINVESTAV-IPN Unidad Guadalajara Av. del Bosque 1145 CP 45019 Zapopan Jalisco Mexico DIIS/I3A Univ. de Zaragoza María de Luna 1 - 50018 Zaragoza España

This work exploits Timed Continuous Petri Nets (TCPN) to design and test a novel energy-efficient thermal-aware real-time global scheduler for a hard real-time (HRT) task set running on a multiprocessor system. The TCPN model encompasses both the system and task set, including thermal features. In previous work we calculated the share of each task that must be executed per time interval by solving off-line an Integer programming problem problem (ILP). A subsequent on-line stage allocated jobs to processors. We now perform the allocation off-line too, including an allocation controller and an execution controller in the on-line stage. This adds robustness by ensuring that actual task allocation and execution honor the safe schedule provided off-line. Last, the on-line controllers allow the design of an improved soft RT aperiodic task manager. Also, we experimentally prove that our scheduler yields fewer context switches and migrations on the HRT task set than RUN, a reference algorithm.

关键词： Real Time Scheduling Petri Net linear programming problem Unimodularity

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Mega-Solar Optimal Allocation Using Data Envelopment Analysis

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ELECTRICAL ENGINEERING IN JAPAN 2013年第4期183卷 24-32页

作者： Yokota, Shinya Kumano, Teruhisa Meiji Univ Tokyo 101 Japan

In this paper, the optimal allocation of mega-solar is examined using data envelopment analysis (DEA). A great deal of attention is paid to photovoltaic power generation in Japan. Because such power generation can be freely used, it is attractive in Japan, which has few natural resources. The allocation of mega-solar, a large-scale photovoltaic power generation method, is an important problem for meeting the hope of efficient operation. We tried to apply DEA in Shizuoka Prefecture and to solve this issue. In this type of DEA application, some analyses often result in zero weighting factors in the parameters of some items to be studied, which implies that the corresponding items are not appropriately evaluated. The existing studies do not give special consideration to this situation. In this study, a new calculation scheme is proposed, the above-stated problems are successfully resolved, and the optimal candidate sites have been selected for the mega-solar allocation. (C) 2013 Wiley Periodicals, Inc. Electr Eng Jpn, 183(4): 24-32, 2013;Published online in Wiley Online Library (***). DOI 10.1002/eej.22322

关键词： data envelopment analysis (DEA) mega-solar location optimization linear programming problem decision-making unit sensitivity analysis

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Optimal Channel Selection algorithm for CRahNs

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PHYSICAL COMMUNICATION 2022年 54卷

作者： Pal, Raghavendra Dahiya, Suresh Sardar Vallabhbhai Natl Inst Technol Dept Elect Engn Surat 395007 Gujarat India

As the data traffic is increasing, the spectrum bands are getting congested. It causes low latency and unreliable communication. Additional spectrum can be utilized to solve this problem but moving towards higher frequency means higher power requirement and increased cost. Cognitive radio network is another solution to this problem. It helps the nodes of a network to use the channels of the nearby bands which are not being used at that time. However, it has several challenges. One of these challenges is the transmission collision with the primary users of the network. Researchers have been working on this problem. However, it is still a major concern for the researchers. This paper proposes an algorithm that selects the optimal cognitive channel for the data transmission by the secondary user in such a way so that the transmission collision with the PU is minimized. After comparison with the existing latest similar protocol, the proposed protocol has shown 5.6% improvement in the throughput, 5.3% improvement in PDR. The delay is decreased by 0.6% and the transmission collision with PUs is reduced by 2.5%. (c) 2022 Elsevier B.V. All rights reserved.

关键词： linear programming problem Dynamic spectrum access Cognitive radio ad hoc networks Spectrum Hsandoff

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A Dynamic Constraint-based Modelling (DCBM) Approach With Alternative Metabolic Objective Functions Predicts The impact of Oxidative Stress on Stored Red Blood Cells (RBCs)

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IFAC-PapersOnLine 2022年第20期55卷 385-390页

作者： Mohammadreza Yasemi Michel Prudent Mario Jolicoeur Research Laboratory in Applied Metabolic Engineering Department of Chemical Engineering École Polytechnique de Montréal P.O. Box 6079 Centreville Station Montréal (Québec) H3C 3A7 Canada Laboratoire de Recherche sur les Produits Sanguins Transfusion Interrégionale CRS Epalinges Switzerland Centre de transfusion sanguine Faculté de Biologie et Médecine Université de Lausanne Lausanne Switzerland Center for Research and Innovation in Clinical Pharmaceutical Sciences Lausanne University Hospital and University of Lausanne Lausanne Switzerland

Mathematical metabolic modelling is a systematic endeavour to allow identifying the main causes of an observed metabolic change and to estimate the consequences of an imposed metabolic perturbation regarding a biosystem. Dynamic Constraint-based modelling (DCBM) has delivered promising results in metabolic engineering and in bioprocess design by providing mechanistically relevant systems-level knowledge of a network of bioreactions. Here, we seek to establish a DCBM approach that leverages convex optimization and nonlinear regression mathematical toolkit to estimate dynamic intracellular metabolic flux distributions in stored Red Blood Cells (RBCs) for transfusion purposes. First, we developed an ad-hoc metabolic network including 77 reactions and 74 metabolites, second, we adapted Flux Variability Analysis (FVA) technique to quantify the connection between exometabolomic dynamics and the dynamics of feasible intracellular reaction flux ranges. We have obtained fine-grained flux range dynamics of the intracellular reactions for the benchmark data published in (Bordbar et al., 2016). Then, we defined four objective functions regarding the accumulation of oxidative stress in stored RBCs for performing a dynamic Flux Balance Analysis (DFBA). In all four cases, time-resolved flux predictions were obtained respecting the imposed equality and inequality constraints. Last, we adapted a quadratic programming (QP) approach to calculate the Euclidean distance between the dynamic optimum flux vectors. The DCBM approach we have developed herein along with the developed metabolic network showed being suitable for the computational analysis of RBCs metabolic behaviour, and it is thought to be useful for other biosystems.

关键词： Mathematical programming Biological Systems Modelling Metabolic Network Modelling Constraint-based Modelling linear programming problem Oxidative Stress Red Blood Cells

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APPLICATION OF RECURRENT NEURAL NETWORK USING MATLAB SIMULINK IN MEDICINE

ITALIAN JOURNAL OF PURE AND APPLIED MATHEMATICS

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ITALIAN JOURNAL OF PURE AND APPLIED MATHEMATICS 2018年第39期 23-30页

作者： Das, Raja Reddy, Madhu Sudan VIT Univ Vellore Tamil Nadu India

In this paper, a recurrent neural network (RNN) for finding the solution of linear programming problems is presented with better, spontaneous and fast converging. To achieve optimality in accuracy and also in computational effort, an algorithm is also presented. This paper covers the MATLAB Simulink modeling and simulative confirmation of such a recurrent neural network. Modeling and simulative results validate the theoretical analysis and efficiency of the recurrent neural network for finding the solution for linear programming problem. An application RNN in medicine has been presented to show the performance of the recurrent neural network.

关键词： linear programming problem Recurrent Neural Network (RRN) MATLAB Simulink

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Power Supply Company purchase’ portfolio optimisation considering electric vehicle charging load forecasting

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The Journal of Engineering 2017年第13期2017卷 2530-2534页

作者： Yahong Li Hui Ren School of Electrical and Electronic Engineering North China Electric Power University Baoding 071003 People's Republic of China

In recent years, a large number of electric vehicles (EVs) were used and the deployment of EVs will lead to an increase in load and load uncertainty, which introduces volume risk in the bilateral contracts. In order to assess and hedge the risk, the EVs charging load model and the Power Supply Company purchase’ portfolio optimisation model are proposed. A linear programming problem for the Power Supply Company purchase’ portfolio optimisation with conditional value at risk (CVaR) have been formulated, and it contains load uncertainty caused by EVs load, price fluctuation, and the expected cost of errors. This study analyses optimal portfolio allocations to different markets, efficient frontier of CVaR, and the influence of different EVs market penetration levels on the portfolio strategy. The analysis results show that risk of the market increases as the EVs market penetration level increases. Power Supply Company may hedge risk through adjusting the optimal portfolio allocation to different electricity markets.

关键词： investment pricing power markets load forecasting linear programming electric vehicle charging load uncertainty portfolio strategy optimal portfolio allocation electric vehicle volume risk load model electricity markets EV load optimal portfolio allocations EV market penetration levels power supply company purchase portfolio optimisation model electric vehicle charging load forecasting linear programming problem CVaR

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