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Sdn+K8s Routing optimization Strategy in 5G Cloud Edge Collaboration Scenario

IEEE ACCESS 2023年 11卷 8397-8406页

作者： Yan, Chungang Sheng, Shuo Tongji Univ Key Lab Embedded Syst & Serv Comp Minist Educ Shanghai 201804 Peoples R China

The cloud-edge-collaboration framework in the 5G scenario emerged as the times developing. The horizontal and vertical disassembly of computing power is particularly important, relying on the full life cycle resource allocation and flexible configuration of SDN+K8s+microservice. This paper proposes a new cloud native architecture form under the 5g cloud edge collaboration scenario. At the same time, it optimizes the SDN routing strategy at multiple levels, decouples and integrates context boundaries with the micro service sevicemesh at multiple levels. For the underlying computing power and network form, it performs multi threshold detection and global route optimization based on k8s + Sdn. Experiments prove the stability and reliability of the 5g + cloud edge collaboration architecture and the progressiveness of route optimization.

关键词： Cloud computing Collaboration 5G mobile communication Computer architecture Data centers Protocols Microservice architectures Path planning 5G SDN K8s servicemesh microservice algorithm optimization route optimization strategy

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Design and optimization of driving mode control strategies for front-and-rear-axle-independent-drive-type electric vehicle

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2024年第6期239卷 1987-2003页

作者： Ye, Li-hua Ke, Cheng-long Shi, Ye-fan Zhang, Hou-zhong Cheng, Xing Zhang, Zi-xing Shi, Ai-ping Jiangsu Univ Sch Automot & Traff Engn Zhenjiang Jiangsu Peoples R China Cranfield Univ Cranfield MK43 0AL Beds England Jiangsu Univ Sch Automot & Traff Engn Zhenjiang 212013 Jiangsu Peoples R China

In order to fully exploit the energy-saving advantages of front-and-rear-axle-independent-drive-type electric vehicle (FRID EV) configuration, this paper designs a drive mode control strategy for it. Based on the characteristics of the drive system with FRID EV, this paper categorizes the drive modes into three, and creates a mathematical model to determine the operating range. Then, an improved particle swarm optimization algorithm is used to optimize the torque distribution based on the principle of system efficiency optimality, so as to develop the optimal drive mode switching control strategy after torque optimization. Finally, the whole vehicle model is built in Cruise for joint simulation with MATLAB /Simulink. Results of the simulation indicate that the drive control strategy with improved particle swarm optimization can effectively improve the energy efficiency of the drive system and boost the vehicle economy, when compared to both the simple two-motor torque equalization strategy and the standard particle swarm optimization strategy.

关键词： Dual motor drive efficiency optimization power distribution driving modes algorithm optimization

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GPP-Based Soft Base Station Designing and optimization

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Journal of Computer Science & Technology 2013年第3期28卷 420-428页

作者：陶小峰侯延昭王凯栋何海洋郭英杰 Key Lab of Universal Wireless Communications of Ministry of Education Beijing University of Posts and Telecommunications CSIRO Information and Communication Technologies Centre

It is generally acknowledged that mobile communication base stations are composed of hardware components such as Field Programming Gate Array （FPGA）, Digital Signal Processor （DSP）, which promise reliable and fluent services for the mobile users. However, with the increasing demand for energy-efficiency, approaches of low power-consumption and high-flexibility are needed urgently. In this circumstance, General Purpose Processor （GPP） attracts people＇s attention for its low-cost and flexibility. Benefited from the development of modern GPP in multi-core, Single Instruction Multiple Data （SIMD） instructions, larger cache, etc., GPPs are capable of performing high-density digital processing. In this paper, we compare several software-defined radio （SDR） prototypes and propose the general architecture of GPP-based soft base stations. Then, the schematic design of resource allocation and algorithm optimization in soft base station implementation are studied. As an application example, a prototype of GPP-based soft base station referring to the 3rd Generation Partnership Project （3GPP） Long Term Evolution （LTE） is realized and evaluated. To the best of our knowledge, it is the first Soft-LTE prototype ever reported. In the end, we evaluate the timing performance of the LTE soft base station and a packet loss ratio of less than 0.003 is obtained.

关键词： software radio algorithm optimization long term evolution

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optimization of temperature prediction algorithms and simulation of future neighborhood-scale thermal environments in Chongqing

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BUILDING AND ENVIRONMENT 2024年 266卷

作者： Jiang, Lina Fan, Zhixuan Gao, Yafeng Su, Xing Rashidov, Jasur Chongqing Univ Joint Int Res Lab Green Bldg & Built Environm Minist Educ Chongqing 400044 Peoples R China Tongji Univ Sch Mech Engn 1239 Siping Rd Shanghai 200092 Peoples R China Tashkent Univ Architecture & Civil Engn Fac Technol Yangishakhar St 9 Tashkent Uzbekistan

With climate change and urbanization, predicting the outdoor thermal environment of residential areas has become increasingly crucial, particularly during extreme weather conditions. Existing studies lack a comprehensive approach to optimizing temperature prediction algorithms for Chongqing and simulating extreme thermal environments at the neighborhood scale for future decades. This study employed various algorithms, including Levenberg-Marquardt optimization, Monte Carlo simulation, ARIMA modeling, and SARIMA prediction, to simulate and forecast temperature data for the central urban area of Chongqing from 2014 to 2023. By assessing metrics such as root mean square error (RMSE), R-squared (R2), and mean absolute percentage error (MAPE), the most effective prediction algorithm was identified. Results indicate that the Levenberg-Marquardt optimization algorithm, known for its nonlinear curve fitting capabilities, demonstrated superior performance in both the test and training sets, achieving an RMSE of 0.82 degrees C, MAPE of 1.81 %, and R2 of 0.75. This algorithm was subsequently used to forecast the outdoor temperature trend in Chongqing from 2024 to 2050, while also simulating the outdoor wind field, temperature distribution, building surface temperatures, and wind speeds in a residential district at neighborhood scale for 2030, 2040, and 2050 at a building density of 40 %. Findings reveal that peak pedestrian-level temperatures could reach 45.62 degrees C, and peak roof surface temperatures could reach 93.93 degrees C under extreme conditions. Furthermore, the study proposes practical recommendations for building layouts and cooling strategies. These findings are expected to improve residential planning in Chongqing, enhance residents' quality of life, and provide insights for other regions facing future temperature changes.

关键词： Thermal environment prediction algorithm optimization Chongqing urban planning

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optimization of welding parameters on welding distortion and stress in S690 high-strength steel thin-plate structures

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JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T 2023年 25卷 382-397页

作者： Liu, Shuai Wu, Zhiqiang Liu, Huan Zhou, Honggang Deng, Kangzong Wang, Chuanhui Liu, Longfei Li, Eric Hunan Univ Sci & Technol Engn Res Ctr Min Dev Technol & Equipment Deep Sea Minist Educ Xiangtan 411201 Hunan Peoples R China Zooml Heavy Ind Sci & Technol Co Ltd Changsha 410013 Hunan Peoples R China Jianglu Electromech Sci & Technol Co Ltd Res Inst Technol Xiangtan 411202 Hunan Peoples R China Hexagon Mfg Intelligence Qingdao Co Ltd Qingdao 266114 Peoples R China Teesside Univ Sch Comp Engn & Digital Technol Middlesbrough North Yorkshire England

This study examines the impact of welding heat input on the residual stress and welding deformation of large, thin-walled constructions made of ultra-high strength steel using a single shot calculation method. These structures are susceptible to warpage distortion after welding, which negatively affects production precision. The study uses an interactive orthogonal experimental design to optimize welding parameters and investigate their in-fluence on deformation. Results reveal that welding speed has the most significant impact on deformation, followed by welding voltage and current. The optimal welding parameters (v 1/4 60 cm/min, I 1/4 160 A, U 1/4 16 V) are validated through simulation and experiment, which reduce deformation by 5.4%. After optimization, the pump arm's side bending vol-ume and warpage volume decrease by 4.06% and 9.56%, respectively, and welding defor-mation significantly reduces. Experimental verification shows a maximum error of 2.6%, indicating the accuracy of the finite element model. This study provides a theoretical basis for improving the performance of welding large, thin-walled box structures.& COPY;2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Thin -walled box structure Weld heat input Welding deformation algorithm optimization

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Genetic optimization of Training Sets for Improved Machine Learning Models of Molecular Properties

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JOURNAL OF PHYSICAL CHEMISTRY LETTERS 2017年第7期8卷 1351-1359页

作者： Browning, Nicholas J. Ramakrishnan, Rapunathan von Lilienfeld, O. Anatole Roethlisberger, Ursula Ecole Polytech Fed Lausanne Swiss Fed Inst Technol Inst Chem Sci & Engn Lab Computat Chem & Biochem CH-1015 Lausanne Switzerland Univ Basel Natl Ctr Computat Design & Discovery Novel Mat MA Klingelbergstr 80 CH-4056 Basel Switzerland Univ Basel Dept Chem Inst Phys Chem Klingelbergstr 80 CH-4056 Basel Switzerland Tata Inst Fundamental Res Ctr Interdisciplinary Sci 21 Brundavan Colony Hyderabad 500075 Andhra Prades India

The training of molecular models of quantum mechanical properties based on statistical machine learning requires large data sets which exemplify the map from chemical structure to molecular property. Intelligent a priori selection of training examples is often difficult or impossible to achieve, as prior knowledge may be unavailable. Ordinarily representative selection of training molecules from such data sets is achieved through random sampling. We use genetic algorithms for the optimization of training set composition consisting of tens of thousands of small organic molecules. The resulting machine learning models are considerably more accurate: in the limit of small training sets, mean absolute errors for out-of-sample predictions are reduced by up to similar to 75%. We discuss and present optimized training sets consisting of 10 molecular classes for all molecular properties studied. We show that these classes can be used to design improved training sets for the generation of machine learning models of the same properties in similar but unrelated molecular sets.

关键词： algorithm optimization molecular model SETTING mean absolute error Machine Learning Dataset molecular properties Random sampling

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The Application and Potential of Multi-Objective optimization algorithms in Decision-Making for LID Facilities Layout

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WATER RESOURCES MANAGEMENT 2024年第14期38卷 5403-5417页

作者： Xie, Yuanyuan Wang, Haiyan Wang, Kaiyi Ge, Xiaoyu Ying, Xin Beijing Forestry Univ Sch Informat Sci & Technol Beijing 100083 Peoples R China Beijing Forestry Univ Sch Landscape Architecture Beijing 100083 Peoples R China Beijing BLDJ Landscape Architecture Inst Co LTD Beijing 100083 Peoples R China

Low-impact development (LID) practices are critical for mitigating urban stormwater runoff and alleviating flood risks. The strategic placement of LID facilities is paramount to optimizing their efficacy within urban landscapes. This study conducts a comprehensive bibliometric analysis of LID-related literature over the past decade, utilizing data visualization tools to elucidate key disciplines, publication trends, and the prevalence of various optimization algorithms. We delve into the application of multi-objective optimization (MOO) algorithms in LID facility layout, examining their practical applications, theoretical underpinnings, and case studies. The paper also scrutinizes the strengths and limitations of these algorithms, proposing future research trajectories that leverage MOO to enhance LID's role in urban stormwater management.

关键词： Low-impact Development algorithm optimization Multi-objective optimization Genetic algorithms Layout Decision

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USING RESERVES OF COMPUTING optimization TO SOLVE COMPLEX PROBLEMS

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CYBERNETICS AND SYSTEMS ANALYSIS 2019年第1期55卷 40-54页

作者： Zadiraka, V. K. Natl Acad Sci Ukraine VM Glushkov Inst Cybernet Kiev Ukraine

The paper considers stages of the development of studies in computing optimization in Ukraine (in particular, at the V.M. Glushkov Institute of Cybernetics of the National Academy of Sciences of Ukraine) related to elements of error theory, computational algorithms that are optimal in accuracy and time, high-tech computer technologies for solving problems in computational and applied mathematics with given values of quality characteristics.

关键词： computational algorithm approximate solution approximate solution error algorithm optimization reserves of computing optimization computer technologies

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Newton-Geodesic HMP algorithms for the optimization of Hybrid Systems and the Geometric Properties of Hybrid Value Functions

Newton-Geodesic HMP Algorithms for the Optimization of Hybri...

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51st IEEE Annual Conference on Decision and Control (CDC)

作者： Taringoo, Farzin Caines, Peter E. McGill Univ Dept Elect & Comp Engn Montreal PQ Canada McGill Univ Ctr Intelligent Machines Montreal PQ Canada

ISBN: (纸本)9781467320665

This paper provides algorithms for the optimization of autonomous hybrid systems based on the geometrical properties of switching manifolds. The first and second sections of the paper introduce optimal hybrid control systems and the third section presents the Newton-Geodesic-Hybrid Minimum Principle (HMP) which is an extension of the Gradient Geodesic-HMP algorithm in [4]. In the fourth section, we extend the analysis yielding the Newton-Geodesic-HMP algorithm to relate the difference of the curvatures of the ambient and switching manifolds to second order variations of the hybrid value function. Finally an example is given to illustrate the results.

关键词： hybrid systems Hybrid control systems Manifolds algorithm optimization algorithms

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optimization of broadcasting scheme for the CASoRT system

Optimization of broadcasting scheme for the CASoRT system

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IEEE 75th Vehicular Technology Conference (VTC Spring)

作者： Hou, Shuo Zhong, Xiaofeng Mei, Shunliang Tsinghua Univ Dept Elect Engn Tsinghua Natl Lab Informat Sci & Technol State Key Lab Microwave & Digital Commun Beijing 100084 Peoples R China

ISBN: (纸本)9781467309905;9781467309882

Content Aware Soft Real Time Media Broadcast (CASoRT) is a new solution for information service of cellular network. As the similar distribution of users interest, the data of same content may be accessed and retransmitted frequently in cellular network during certain period of time, which caused the dissipation of both energy and spectrum efficiency. With the development of Data Mining, the CASoRT system could discovers the users common interests and broadcast such content to users who may be interested in. With those users accessing the content locally, the potential retransmission could be avoided and thus it could save energy from carriers view while providing the same real time experience to the users. In this paper, we propose a set of algorithm for the optimization of broadcasting scheme for the CASoRT system to achieve more energy efficiency.

关键词： broadcasting Information Services algorithm optimization Cellular networks time periods Energy sources

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