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Resource scheduling techniques in cloud from a view of coordination:a holistic survey

Frontiers of Information technology & Electronic Engineering 2023年第1期24卷 1-40页

作者： Yuzhao WANG Junqing YU Zhibin YU School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Center of Heterogeneous Intelligent Computer Architecture and Systems Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China

Nowadays,the management of resource contention in shared cloud remains a pending *** evolution and deployment of new application paradigms(e.g.,deep learning training and microservices)and custom hardware(e.g.,graphics processing unit(GPU)and tensor processing unit(TPU))have posed new challenges in resource management system *** solutions tend to trade cluster efficiency for guaranteed application performance,e.g.,resource over-allocation,leaving a lot of resources *** this dilemma is not easy,because different components across the software stack are ***,massive efforts have been devoted to seeking effective performance isolation and highly efficient resource *** goal of this paper is to systematically cover related aspects to deliver the techniques from the coordination perspective,and to identify the corresponding trends they ***,four topics are ***,isolation mechanisms deployed at different levels(micro-architecture,system,and virtualization levels)are reviewed,including GPU multitasking ***,resource scheduling techniques within an individual machine and at the cluster level are investigated,***,GPU scheduling for deep learning applications is described in ***,adaptive resource management including the latest microservice-related research is thoroughly ***,future research directions are discussed in the light of advanced *** hope that this review paper will help researchers establish a global view of the landscape of resource management techniques in shared cloud,and see technology trends more clearly.

关键词： Coordination Co-location Heterogeneous computing Microservice Resource scheduling techniques

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DrivingSphere: Building a High-fidelity 4D World for Closed-loop Simulation

arXiv

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arXiv 2024年

作者： Yan, Tianyi Wu, Dongming Han, Wencheng Jiang, Junpeng Zhou, Xia Zhan, Kun Xu, Cheng-Zhong Shen, Jianbing SKL-IOTSC Computer and Information Science University of Macau China Li Auto Inc School of Computer Science Beijing Institute of Technology China

Autonomous driving evaluation requires simulation environments that closely replicate actual road conditions, including real-world sensory data and responsive feedback loops. However, many existing simulations need to predict waypoints along fixed routes on public datasets or synthetic photorealistic data, i.e., open-loop simulation usually lacks the ability to assess dynamic decision-making. While the recent efforts of closed-loop simulation offer feedback-driven environments, they cannot process visual sensor inputs or produce outputs that differ from real-world data. To address these challenges, we propose DrivingSphere, a realistic and closed-loop simulation framework. Its core idea is to build 4D world representation and generate real-life and controllable driving scenarios. In specific, our framework includes a Dynamic Environment Composition module that constructs a detailed 4D driving world with a format of occupancy equipping with static backgrounds and dynamic objects, and a Visual Scene Synthesis module that transforms this data into high-fidelity, multi-view video outputs, ensuring spatial and temporal consistency. By providing a dynamic and realistic simulation environment, DrivingSphere enables comprehensive testing and validation of autonomous driving algorithms, ultimately advancing the development of more reliable autonomous cars. The benchmark will be publicly released. https://***/DrivingSphere/ © 2024, CC BY-NC-SA.

关键词： Autonomous vehicles

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Mixture of Experts as Representation Learner for Deep Multi-View Clustering 39

Mixture of Experts as Representation Learner for Deep Multi-...

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Zhang, Yunhe Cai, Jinyu Wu, Zhihao Wang, Pengyang Ng, See-Kiong Department of Computer and Information Science SKL-IOTSC University of Macau China Institute of Data Science National University of Singapore Singapore College of Computer Science and Technology Zhejiang University China

ISBN: (纸本)157735897X

Multi-view clustering (MVC) aims to integrate information from diverse data sources to facilitate the clustering process, which has achieved considerable success in various real-world applications. However, previous MVC methods typically employ one of two strategies: (1) designing separate feature extraction pipelines for each view, which restricts their ability to fully exploit collaborative potential;or (2) employing a single shared representation module, which hinders the capture of diverse, view-specific representations. To tackle these challenges, we introduce Deep Multi-View Clustering via Collaborative Experts (DMVC-CE), a novel MVC approach that employs the Mixture of Experts (MoE) framework. DMVC-CE incorporates a gating network that dynamically selects multiple experts for handling each data sample, capturing diverse and complementary information from different views. Additionally, to ensure balanced expert utilization and maintain their diversity, we introduce an equilibrium loss and a multi-expert distinctiveness enhancer. The equilibrium loss prevents excessive reliance on specific experts, while the distinctiveness enhancer encourages each expert to specialize in different aspects of the data, thereby promoting diversity in learned representations. Comprehensive experiments on various multi-view benchmark datasets demonstrate the superiority of DMVC-CE compared to state-of-the-art MVC baselines. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Deep learning

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Application of residual network in household waste classification

Application of residual network in household waste classific...

引用

2023 IEEE International Conference on Control, Electronics and computer technology, ICCECT 2023

作者： Guo, Yutong Luo, Jie Guo, Weile Chengdu University of Technology College of Computer Science Cyber Security Oxford Brookes College Chengdu China Xi'An University of Architecture and Technology College of Metallurgical Engineering Xi'an China

ISBN: (纸本)9798350399028

With the acceleration of urbanization, the amount of garbage has skyrocketed. This makes the burden of sorting waste by manual means heavier and heavier, resulting in a large amount of waste accumulation. In this context, the classification of household garbage gradually received attention. In order to improve the efficiency of garbage classification, we should deal with the increasingly complicated garbage classification work and make garbage classification intelligent and efficient. In this paper, convolutional neural network intelligent algorithm is used to solve the classification problem of organic and inorganic garbage in daily life. The accuracy can reach 90.34% only with low sequence training. Compared with existing commonly used garbage classification and recognition algorithms, the proposed garbage classification and recognition algorithm has better recognition performance and is more suitable for widespread application. © 2023 IEEE.

关键词： Image classification

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Distributed Voltage Regulation of Distribution Network Based on Partition Control 2

Distributed Voltage Regulation of Distribution Network Based...

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2nd International Conference on Cyber-Energy Systems and Intelligent Energy, ICCSIE 2024

作者： Jine, Wang Hui, Chen Liying, Zhao Guangxin, Zhang School of Electrical Information Changchun University of Architecture and Civil Engineering Changchun City China School of Computer Technology and Engineering Changchun Institute of Technology Changchun City China School of Information and Engineering College of Science & Technology Ningbo University Ningbo City China

ISBN: (纸本)9798350373318

As china's social economy progresses, the amount of equipment in distribution networks continues to grow, leading to increasingly complex system operations. In this environment, traditional centralized control methods consume excessive computing resources and fail to achieve the processing speeds required by modern intelligent distribution networks. To address these challenges, this article introduces the concept of electrical distance to segment the distribution network and proposes voltage regulation algorithms based on the alternating direction multiplier method and dual ascent method for efficient distributed voltage regulation. © 2024 IEEE.

关键词： DC distribution systems

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Research on face video generation algorithm based on speech content 2

Research on face video generation algorithm based on speech ...

引用

2nd International Conference on Image Processing, computer Vision and Machine Learning, ICICML 2023

作者： Pan, Qunqin Zhang, Chao Wu, Chengqin Chen, Liangyu Sun, Yulin Changchun University of Science and Technology School of Computer Science and Technology Jilin Province Changchun City China Shanghai Ocean University College of Engineering Science and Technology Shanghai China Jilin Jianzhu University School of Architecture and Planning Jilin Province Changchun City China

ISBN: (纸本)9798350331417

Aiming at the problem that the audio and lip motion are not synchronized and the face appears white light in the speech-driven face speech video, the audio-visual synchronization module and the highlight noise reduction module are proposed on the basis of the Wav2Lip network. Firstly, the sound visual alignment module is added to make the model learn the context information of the speech signal in the forward and backward directions, so as to improve the accuracy of lip synchronization. Secondly, in the image encoder, the highlight noise reduction module (HDM) is introduced to solve the problem of noise and overexposure in the highlight area of the generated speech face video. The experimental results on the LRS2 dataset show that the confidence score (LSE-C), the deviation index (LSE-D) and the image structure similarity (SSIM) of the audio-visual quality alignment network (AVQA) in this paper reach 8.565 and 4.605 and 0.872 respectively. © 2023 IEEE.

关键词： Audio-visual synchronization module High light noise reduction module Talking face video

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Citrus objects recognition in orchard scene using HSV methods

Citrus objects recognition in orchard scene using HSV method...

引用

2024 International Conference on Image Processing and Artificial Intelligence, ICIPAl 2024

作者： Hua, Yanzhi Wu, Shuqin Liang, Liling Jiang, Minghui Fan, Yong Xie, Wu School of Mechanical and Electrical Engineering Guilin University of Electronic Technology Guilin541004 China School of Architecture and Transportation Engineering Guilin University of Electronic Technology Guilin541004 China School of Computer Science and Information Security Guilin University of Electronic Technology Guilin541004 China

ISBN: (纸本)9781510681514

There is a problem that it is always difficult for picking and spraying robots to identify the objects for such factors such as leaf occlusion, similar color and others. In this paper, based on the citrus image data set collected from the actual orchard scene, image features are extracted and a mathematical model is constructed to identify and count the number of citruses in each image, and the distribution of apples in the whole data set is displayed. A model is constructed to be used to identify and count citrus via these images with diversity of citrus colors and the complexity of the background. Firstly, the yellow mature citruses are focused on using the HSV (Hue, Saturation, Value) method for the data sets. Secondly, the empirical HSV range for two citrus fruits, cyan and yellow, was defined, and contour processing is introduced to optimize the recognition model to process more citrus image datasets. Finally, such three types of objects as immature citrus, leaves with similar colors, and citrus covered by leaves are distinguish. The research results indicate that we adopt more detailed color threshold settings and morphological operations with the eccentricity of the contour is less than 0.85, and can distinguish citrus and leaves through image segmentation,and the recognition effect on citrus objects is improved. © 2024 SPIE.

关键词： Morphology

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Bootstrapping Referring Multi-Object Tracking

arXiv

引用

arXiv 2024年

作者： Zhang, Yani Wu, Dongming Han, Wencheng Dong, Xingping School of Computer Science Wuhan University China Beijing Institute of Technology China SKL-IOTSC CIS University of Macau China

Referring multi-object tracking (RMOT) aims at detecting and tracking multiple objects following human instruction represented by a natural language expression. Existing RMOT benchmarks are usually formulated through manual annotations, integrated with static regulations. This approach results in a dearth of notable diversity and a constrained scope of implementation. In this work, our key idea is to bootstrap the task of referring multi-object tracking by introducing discriminative language words as much as possible. In specific, we first develop Refer-KITTI into a large-scale dataset, named Refer-KITTI-V2. It starts with 2,719 manual annotations, addressing the issue of class imbalance and introducing more keywords to make it closer to real-world scenarios compared to Refer-KITTI. They are further expanded to a total of 9,758 annotations by prompting large language models, which create 617 different words, surpassing previous RMOT benchmarks. In addition, the end-to-end framework in RMOT is also bootstrapped by a simple yet elegant temporal advancement strategy, which achieves better performance than previous approaches. The source code and dataset is available at https://***/zyn213/TempRMOT. Copyright © 2024, The Authors. All rights reserved.

关键词： Large datasets

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A Provably Secure Lightweight Key Agreement Protocol for Wireless Body Area Networks in Healthcare System

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IEEE Transactions on Industrial Informatics 2023年第2期19卷 1683-1690页

作者： Zia, Maryam Obaidat, Mohammad S. Mahmood, Khalid Shamshad, Salman Saleem, Muhammad Asad Chaudhry, Shehzad Ashraf Comsats University Islamabad Department of Computer Science Sahiwal57000 Pakistan University of Jordan King Abdullah Ii School of Information Technology Amman11942 Jordan University of Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China Amity University UP Noida201301 India National Yunlin University of Science and Technology Future Technology Research Center Yunlin64002 Taiwan The University of Lahore Department of Software Engineering Lahore54590 Pakistan Abu Dhabi University Department of Computer Science and Information Technology College of Engineering Abu Dhabi United Arab Emirates Nisantasi University Department of Computer Engineering Faculty of Engineering and Architecture Istanbul34398 Turkey

Wireless Body Area Network (WBAN) is a vital application of the Internet of Things (IoT) that plays a significant role in gathering a patient's healthcare information. This collected data helps special professionals like doctors or physicians analyze patients' health status to cure different diseases. However, collecting such information from an insecure channel can be threatening due to the potential security threats. Therefore, it is crucial to secure this sensitive information. This article proposes a secure and lightweight authentication protocol for WBAN. The devised protocol is scalable, secure, and lightweight compared to various relevant competing protocols. The informal security analysis shows that the designed protocol is lightweight, secure, and efficient in resisting various major attacks. The performance analysis demonstrates our protocol's supremacy over various competing protocols in terms of computation and communication costs, inducing efficiency of 20.3% and 12.3%, respectively. Moreover, the practical performance of the designed protocol from the network point of view is measured using the widely recognized NS3 simulation tool. © 2005-2012 IEEE.

关键词： Authentication

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Deadline and Priority Constrained Immersive Video Streaming Transmission Scheduling

arXiv

引用

arXiv 2024年

作者： Feng, Tongtong Qi, Qi He, Bo Wang, Jingyu Department of Computer Science and Technology Tsinghua University Beijing China SKL-NST Beijing University of Posts and Telecommunications Beijing China

Deadline-aware transmission scheduling in immersive video streaming is crucial. The objective is to guarantee that at least a certain block in multi-links is fully delivered within their deadlines, which is referred to as delivery ratio. Compared with existing models that focus on maximizing throughput and ultra-low latency, which makes bandwidth resource allocation and user satisfaction locally optimized, immersive video streaming needs to guarantee more high-priority block delivery within personalized deadlines. In this paper, we propose a deadline and priority-constrained immersive video streaming transmission scheduling scheme. It builds an accurate bandwidth prediction model that can sensitively assist scheduling decisions. It divides video streaming into various media elements and performs scheduling based on the user’s personalized latency sensitivity thresholds and the media element’s priority. We evaluate our scheme via trace-driven simulations. Compared with existing models, the results further demonstrate the superiority of our scheme with 12%-31% gains in quality of experience (QoE). Copyright © 2024, The Authors. All rights reserved.

关键词： Bandwidth

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