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Instant queue occupancy used for automatic traffic scheduling in data center networks

Computer Networks 2024年 244卷

作者： Iqbal, Muhammad Shahid Chen, Chien EECS International Graduate Program National Yang Ming Chiao Tung University Hsinchu Taiwan Information Technology Service Center and Department of CS National Yang Ming Chiao Tung University Hsinchu Taiwan

Datacenter applications desire low latency for short messages to provide a better user experience. Therefore, one of the goals of datacenter networks is to minimize flow completion time (FCT), especially for short flows. Multiple scheduling disciplines have been proposed to achieve this goal. In this paper, we develop a Dynamic Longer Stay Less Priority (D-LSLP) which looks at the current queue occupancy to adjust the demotion threshold for the packets of the flows arriving in the strict priority queues. Initially, D-LSLP considers every flow to be a short flow, and with the passage of time, the flow is demoted to the lower priority queue, similar to Multilevel Feedback Queue (MLFQ) Scheduling. It enables short flows to be completed in a couple of higher-priority queues. In contrast, large flows are demoted to the lower priority queues after remaining active in the queues for a certain amount of time (demotion threshold). However, for the different traffic patterns with different distribution of flow lengths, the demotion threshold for the flows should be adapted automatically. In this paper, we leverage the programmable nature of the P4 switches to measure the instant queue occupancy in the P4, which can be used to adjust the demotion threshold accordingly for the highest priority queue. This enables D-LSLP to increase or decrease its highest priority demotion threshold based on the instant queue status. D-LSLP allows multiple traffic patterns to coexist without manually tuning the demotion thresholds. Furthermore, it reduces the tail drop in the highest priority queue when many short flows overwhelm the highest priority queue. The performance evaluation shows that it works equally well for different traffic patterns without operator intervention. © 2024

关键词： Queueing theory

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How a Global Elective Engineering class impacts Engineering Students' Global Efficacy

How a Global Elective Engineering class impacts Engineering ...

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2023 IEEE IFEES World Engineering Education Forum and Global Engineering Deans Council, WEEF-GEDC 2023

作者： Gurganus, Jamie R. Malschutzky, Michael M. Do Carmo Santos, Joao Carlos Zupan, Marc Dos Santos, Abel Dias Engineering & Computing Education Program & Graduate School Baltimore United States Centre for Teaching Development and Innovation Department of Management Sciences Hochschule Bonn-Rhein-Sieg Sankt Augustin Germany College of Engineering and Information Technology Department of Mechanical Engineering Baltimore United States Departamento de Engenharia Mecânica Porto Portugal

ISBN: (纸本)9798350316025

Today's pluralistic and globalized society requires a global perspective in how we think, view ourselves, and relate to others to collaborate successfully with people with different cultural backgrounds. To support the development of a global perspective, universities cultivate international co-operations to enable international mobility for students, faculty, and staff. However, in-person mobility can be inhibited due to various reasons. To support a wider pool of students gaining international experience, modern digital mediated course formats can be used to offer virtual instead of in-person mobility. This contribution evaluates a digital mediated course for mechanical engineering students (Global Engineering, GE) held in co-operation between an US and a Portuguese university, where internationally mixed student groups working on design projects in an Hyflex setting. Asides a literature driven discussion about the need for Global Engineers and a detailed description of the GE course, a longitudinal analysis was performed to assess the impact of the GE course on the students' development of a global perspective. The longitudinal analysis showed strong statistical support that the digitally mediated GE course improved the participating students' global perspective, assessed with the Global Perspective Inventory (GPI), tremendously. The observed improvements were in three of the six GPI dimensions comparable to an in-person semester abroad. Limitations of the study and future investigations are discussed. © 2023 IEEE.

关键词： Students

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Variable-Speed Teaching-Playback as Real-World Data Augmentation for Imitation Learning

arXiv

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arXiv 2024年

作者： Masuya, Nozomu Sato, Hiroshi Yamane, Koki Kusume, Takuya Sakaino, Sho Tsuji, Toshiaki Master's Program in Intelligent and Mechanical Interaction Systems Degree Programs in Systems and Information and Engineering Graduate School of Science and Technology University of Tsukuba Japan Doctoral Program in Intelligent and Mechanical Interaction Systems Degree Programs in Systems and Information and Engineering Graduate School of Science and Technology University of Tsukuba Japan Department of Intelligent Interaction Technologies Institute of Systems and Information Engineering University of Tsukuba Japan Graduate School of Science and Engineering Saitama University Saitama Japan

Because imitation learning relies on human demonstrations in hard-to-simulate settings, the inclusion of force control in this method has resulted in a shortage of training data, even with a simple change in speed. Although the field of data augmentation has addressed the lack of data, conventional methods of data augmentation for robot manipulation are limited to simulation-based methods or downsampling for position control. This paper proposes a novel method of data augmentation that is applicable to force control and preserves the advantages of real-world datasets. We applied teaching-playback at variable speeds as real-world data augmentation to increase both the quantity and quality of environmental reactions at variable speeds. An experiment was conducted on bilateral control-based imitation learning using a method of imitation learning equipped with position-force control. We evaluated the effect of real-world data augmentation on two tasks, pick-and-place and wiping, at variable speeds, each from two human demonstrations at fixed speed. The results showed a maximum 55% increase in success rate from a simple change in speed of real-world reactions and improved accuracy along the duration/frequency command by gathering environmental reactions at variable speeds. Copyright © 2024, The Authors. All rights reserved.

关键词： Demonstrations

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CAMRI Loss: Improving the Recall of a Specific Class without Sacrificing Accuracy

CAMRI Loss: Improving the Recall of a Specific Class without...

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作者： Nishiyama, Daiki Fukuchi, Kazuto Akimoto, Youhei Sakuma, Jun Master's Program in Computer Science Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Tsukuba-shi305-8577 Japan RIKEN Center for Advanced Intelligence Project Tokyo103-0027 Japan Department of Computer Science Faculty of Engineering Information and Systems University of Tsukuba Tsukuba-shi305-8577 Japan

In real world applications of multiclass classification models, misclassification in an important class (e.g., stop sign) can be significantly more harmful than in other classes (e.g., no parking). Thus, it is crucial to improve the recall of an important class while maintaining overall accuracy. For this problem, we found that improving the separation of important classes relative to other classes in the feature space is effective. Existing methods that give a class-sensitive penalty for cross-entropy loss do not improve the separation. Moreover, the methods designed to improve separations between all classes are unsuitable for our purpose because they do not consider the important classes. To achieve the separation, we propose a loss function that explicitly gives loss for the feature space, called class-sensitive additive angular margin (CAMRI) loss. CAMRI loss is expected to reduce the variance of an important class due to the addition of a penalty to the angle between the important class features and the corresponding weight vectors in the feature space. In addition, concentrating the penalty on only the important class hardly sacrifices separating the other classes. Experiments on CIFAR-10, GTSRB, and AwA2 showed that CAMRI loss could improve the recall of a specific class without sacrificing accuracy. In particular, compared with GTSRB's second-worst class recall when trained with cross-entropy loss, CAMRI loss improved recall by 9%. © 2023 The Institute of Electronics, information and Communication Engineers.

关键词： Deep learning

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An ANN-Based Electronic Nose for Monitoring Pollutant Gases in Landfills

An ANN-Based Electronic Nose for Monitoring Pollutant Gases ...

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IEEE Instrumentation and Measurement technology Conference

作者： Juliene dos Santos Davi Muniz Francisco Auriberto Ferreira Marques Junior Cleonilson Protasio De Souza William De Paiva Post-Graduate Program of Electrical Engineering Federal University of Paraíba João Pessoa PB Brazil Post-Graduate Program of Environmental Science and Technology State University of Paraíba Campina Grande PB Brazil Department of Electrical Engineering Federal University of Paraíba João Pessoa PB Brazil Department of Sanitary and Environmental Engineering State University of Paraíba João Pessoa PB Brazil

ISBN: (数字)9798350380903

ISBN: (纸本)9798350380910

Biogas generated from urban solid waste degradation in landfills is composed of various types of gases, some of them are very toxic and harmful to the health of both humans and animals, and contribute directly to global warming as well. In this way, the monitoring of biogas concentration in landfills and their surroundings is very important because this can assess the air contamination around landfills, as well as to propose means to minimize it. In this work, an electronic nose for gas identification and measurement of gases present in landfill biogas using an Artificial Neural Network (ANN) is introduced. The ANN training data have been collected by the developed electronic nose, which consisted on a set of low-cost gas sensors and on a signal acquisition system controlled by the LabViewsoftware. After the ANN training, a neural architecture has been obtained and implemented in a microcontrolled digital system to measure different gas concentrations, mainly, methane. The main results of the proposed ANN-based Electronic Nose show that it was possible to measure the gases concentrations, with RMSE less than 1%, for the most of target gases, confirming the accuracy of the developed system.

关键词： Gases Semiconductor device measurement Accuracy Landfills Artificial neural networks Electronic noses Biogas

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Disease Data Modeling by Using Machine Learning Approach

Disease Data Modeling by Using Machine Learning Approach

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International Conference on information technology, Computer and Electrical Engineering (ICITACEE)

作者： Gunawan Wang Rakha Gusti Wardhana Farida Sibuea Anderes Gui Information Systems Management Department BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta Indonesia Head of Data Analytics department Data and Information Technology Centre (Pusdatin) Ministry of Health Jakarta Indonesia School of Information Systems Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350389302

ISBN: (纸本)9798350389319

Since Covid outbreak in 2020, Indonesian Ministry of Health (MoH) has intensively embraced digital transformation initiatives in healthcare management and decision-making process. The latest healthcare digital transformation roadmap 2024, has emphasized the use of AI technology in data analytics and support policy making. The article examines the use of common Machine Learning (AI) algorithms, such as: Logistic Regression, Random Forest, Support Vector Machine (SVM), Decision Tree, and XGBoost. The article applies these algorithms to analyse the common diseases faced by Indonesian such as Measles, Malaria, Leprosy, and Diphtheria. Those diseases are classical diseases, however, still infecting many people in large areas. The article takes a case study of national health profile within period 2017–2022, to study the data model of those diseases. The outcome of the article is expected to be used for further policy making.

关键词： Support vector machines Logistic regression Machine learning algorithms Malaria Measles Medical services Predictive models Prediction algorithms Decision trees Random forests

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Three-dimensional magnetization reconstruction from electron optical phase images with physical constraints

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Science China(Physics,Mechanics & Astronomy) 2024年第11期67卷 122-132页

作者： Boyao Lyu Shihua Zhao Yibo Zhang Weiwei Wang Fengshan Zheng Rafal E.Dunin-Borkowski Jiadong Zang Haifeng Du Anhui Province Key Laboratory of Low-Energy Quantum Materials and Devices High Magnetic Field LaboratoryHefei Institutes of Physical ScienceChinese Academy of SciencesHefei 230031China Science Island Branch Graduate School of University of Science and Technology of ChinaHefei 230026China Department of Physics and Astronomy University of New HampshireDurham 03824USA Department of Physics The City College of New YorkNew York 10031USA Physics Program Graduate Center of the City University of New YorkNew York 10016USA Department of Chemistry University of New HampshireDurham 03824USA Institutes of Physical Science and Information Technology Anhui UniversityHefei 230601China Spin-X Institute Center for Electron MicroscopySchool of Physics and OptoelectronicsState Key Laboratory of Luminescent Materials and DevicesGuangdong-Hong Kong-Macao Joint Laboratory of Optoelectronic and Magnetic Functional MaterialsSouth China University of TechnologyGuangzhou 511442China Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons Forschungszentrum JülichJülich 52425Germany

The ability to characterize three-dimensional(3D)magnetization distributions in nanoscale magnetic materials and devices is essential to fully understand their static and dynamic magnetic *** contrast techniques in the transmission electron microscope(TEM),such as electron holography and electron ptychography,can be used to record two-dimensional(2D)projections of the in-plane magnetic induction of 3D nanoscale *** the 3D magnetic induction can in principle be reconstructed from one or more tilt series of such 2D projections,conventional tomographic reconstruction algorithms do not recover the 3D magnetization within a sample ***,we use simulations to describe the basis of an improved model-based algorithm for the tomographic reconstruction of a 3D magnetization distribution from one or more tilt series of electron optical phase images recorded in the *** algorithm allows a wide range of physical constraints,including a priori information about the sample geometry and magnetic parameters,to be *** also makes use of minimization of the micromagnetic energy in the loss *** demonstrate the reconstruction of the 3D magnetization of a localized magnetic soliton—a hopfion ring—and discuss the influence of noise,choice of magnetic constants,maximum tilt angle and number of tilt axes on the *** algorithm can in principle be adapted for other magnetic contrast imaging techniques in the TEM,as well as for other magnetic characterization techniques,such as those based on X-rays or neutrons.

关键词： three-dimensional magnetization vector field tomography differentiable programming electron holography micromagnetism

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Find the Best Rule of Time Series Data Mining with Cluster Analysis 3

Find the Best Rule of Time Series Data Mining with Cluster A...

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3rd International Conference on Computational Science and information Management, ICoCSIM 2019

作者： Buaton, Relita Zarlis, Muhammad Mawengkang, Herman Efendi, Syahril Graduate Program of Computer Science Department of Computer Science Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

Data mining is an analytical process of knowledge discovery in large and complex data sets. Many studies wish to explore data, to find information so that knowledge can be obtained through the grouping process, classification, rules discovery, associations and data mining visualization which shows similarity. Periodic data often occurs in business applications and sciences that has big size, high dimension and continuously updated. The similarity in periodic data is based on several approaches. One of common approaches is to transform periodic series into other domains so that dimensions are reduced, followed by index mechanism. Many studies of time series do not give optimal result because limited to extracting data not able to represent time series and its pattern which is then change into rules. Rules can be found in time series data, but they are still constrained by over fitting and difficult to present. It causes time series data and non linier function of data mining decision can't be optimal. The basic idea in the method proposed is to do periodic discretization for sub-sequential formation. These sub-sequences are grouped through a measure of similarity. The simple rule-finding technique is applied to obtain hidden rules in the temporal pattern. The optimal time series data expected to generate the uncertainty trend, previously unknown and can be used to make decisions or forecasting in the future. © Published under licence by IOP Publishing Ltd.

关键词： Data mining

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How Panel Layouts Define Manga: Insights from Visual Ablation Experiments

arXiv

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arXiv 2024年

作者： Feng, Siyuan Yoshinaga, Teruya Hayashi, Katsuhiko Washio, Koki Kamigaito, Hidetaka The University of Tokyo Department of Language and Information Sciences Tokyo Japan Sophia University Graduate Degree Program of Applied Data Sciences Tokyo Japan Nara Institute of Science and Technology Division of Information Science Nara Ikoma Japan

Today, manga has gained worldwide popularity. However, the question of how various elements of manga, such as characters, text, and panel layouts, reflect the uniqueness of a particular work, or even define it, remains an unexplored area. In this paper, we aim to quantitatively and qualitatively analyze the visual characteristics of manga works, with a particular focus on panel layout features. As a research method, we used facing page images of manga as input to train a deep learning model for predicting manga titles, examining classification accuracy to quantitatively analyze these features. Specifically, we conducted ablation studies by limiting page image information to panel frames to analyze the characteristics of panel layouts. Through a series of quantitative experiments using all 104 works, 12 genres, and 10,122 facing page images from the Manga109 dataset, as well as qualitative analysis using Grad-CAM, our study demonstrates that the uniqueness of manga works is strongly reflected in their panel layouts. © 2024, CC BY.

关键词： Ablation

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An Efficient Anonymous Authentication Technique for TMIS under the Smart Home Environment

An Efficient Anonymous Authentication Technique for TMIS und...

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2023 IEEE International Conference on Computer, information, and Telecommunication Systems, CITS 2023

作者： Meshram, Chandrashekhar Obaidat, Mohammad S. Sadoun, Balqies Tambare, Parkash Imoize, Agbotiname Lucky Jayawanti Haksar Government Post Graduate College College of Chhindwara University Department of Post Graduation Studies and Research in Mathematics M.P Betul460001 India The University of Jordan Amman Jordan University of Science and Technology Beijing Beijing China College of Engineering Al-Balqa' Applied University Jordan Wram Research Lab Pvt. Ltd. Nagpur440027 India University of Lagos Faculty of Engineering Department of Electrical and Electronics Engineering Akoka Lagos00213 Nigeria Institute of Digital Communication Ruhr University Department of Electrical Engineering and Information Technology Bochum44801 Germany

ISBN: (纸本)9798350336092

The Internet of Things (IoT) is rapidly evolving, and one new paradigm is the 'smart home,' which allows people to control their intelligent home gadgets from anywhere in the world via the Internet. Sensitive information gathered by smart devices is at risk of being intercepted and exploited unlawfully by a malicious third party due to insecure communication routes between the client and the smart devices. Through Telecare Medical information Systems (TMIS), patients can get several types of healthcare delivery services in the comfort of their homes. Access to Electronic Medical Records (EMR) by patients or clinicians requires authentication, patient privacy protection, security, and data confidentiality. Thus, developing an effective anonymous authentication mechanism is crucial to ensure secure communications in the smart home setting. This paper describes a novel and effective security scheme using extended Chebyshev chaotic maps in the context of smart home environments. Analytical results show that the proposed authentication technique is secure from replay attacks, impersonation attacks, offline password guessing attacks, stolen verification table attacks, patient privacy protection, perfect forward secrecy, and known key security. Finally, the projected authentication technique gives superior results to the preliminary techniques. © 2023 IEEE.

关键词： Authentication

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