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42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Gu, Lin Huang, Junhao Huang, Shaoxing Zeng, Deze Li, Bo Jin, Hai Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Wuhan China China University of Geosciences School of Computer Science Wuhan China Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong

ISBN: (纸本)9798350334142

Container based microservices have been widely applied to promote the cloud elasticity. The mainstream Docker containers are structured in layers, which are organized in stack with bottom-up dependency. To start a microservice, the required layers are pulled from a remote registry and stored on its host server, following the layer dependency order. This incurs long microservice startup time and hinders the performance efficiency. In this paper, we discover that, for the first time, the layer pulling order can be adjusted to accelerate the microservice startup. Specifically, we address the problem on microservice layer pulling orchestration for startup time minimization and prove it as NP-hard. We propose a Longest-chain based Out-of-order layer Pulling Orchestration (LOPO) strategy with low computational complexity and guaranteed approximation ratio. Through extensive real-world trace driven experiments, we verify the efficiency of our LOPO and demonstrate that it reduces the microservice startup time by 22.71% on average in comparison with state-of-the-art solutions. © 2023 IEEE.

关键词： Containers

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AccelES: Accelerating Top-K SpMV for Embedding Similarity via Low-bit Pruning 31

AccelES: Accelerating Top-K SpMV for Embedding Similarity vi...

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31st IEEE International Symposium on High Performance computer Architecture, HPCA 2025

作者： Zhai, Jiaqi Shi, Xuanhua Huang, Kaiyi Ye, Chencheng Hu, Weifang He, Bingsheng Jin, Hai Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Wuhan430074 China National University of Singapore School of Computing 119077 Singapore

ISBN: (纸本)9798331506476

In the realm of recommendation systems, achieving real-time performance in embedding similarity tasks is often hindered by the limitations of traditional Top-K sparse matrix-vector multiplication (SpMV) methods, which suffer from high latency due to inefficient memory access patterns. This paper identifies these critical gaps and introduces AccelES, a novel approach that significantly enhances the efficiency of Top-K SpMV. Our method employs a two-stage calculation scheme: the first stage utilizes a compact, low-bit dataset to quickly identify the most relevant entries, while the second stage performs full-precision calculations solely on this pruned subset, thereby minimizing computational overhead. Furthermore, AccelES incorporates innovative matrix representations, Ultra-CSR and Random-CSR, which optimize memory bandwidth utilization. Experimental results demonstrate that AccelES accelerates performance, surpassing state-of-the-art FPGA, GPU, and CPU solutions by factors of 3.4×, 2.5×, and 153.3×, respectively, under controlled conditions. These advancements not only enhance processing speed but also significantly improve real-time performance in recommendation systems, establishing AccelES as a pivotal contribution to the field of Top-K sparse matrix-vector multiplication. © 2025 IEEE.

关键词： Embeddings

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Application of Recursive Query on Structured Query Language Server

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Journal of Donghua University(English Edition) 2023年第1期40卷 68-73页

作者：荀雪莲 ABHIJIT Sen 姚志强 Library North China Institute of Aerospace EngineeringLangfang 065000China Department of Computer Science&Information System Kwantlen Polytechnic UniversitySurreyCanada School of Computer Science and Engineering North China Institute of Aerospace EngineeringLangfang 065000China

The advantage of recursive programming is that it is very easy to write and it only requires very few lines of code if done *** query language(SQL)is a database language and is used to manipulate *** Microsoft SQL Server 2000,recursive queries are implemented to retrieve data which is presented in a hierarchical format,but this way has its *** table expression(CTE)construction introduced in Microsoft SQL Server 2005 provides the significant advantage of being able to reference itself to create a recursive *** data structures,organizational charts and other parent-child table relationship reports can easily benefit from the use of recursive *** recursive query is illustrated and implemented on some simple hierarchical *** addition,one business case study is brought forward and the solution using recursive query based on CTE is *** the same time,stored procedures are programmed to do the recursion in *** results show that recursive queries based on CTEs bring us the chance to create much more complex queries while retaining a much simpler syntax.

关键词： structured query language(SQL)server common table expression(CTE) recursive query stored procedure hierarchical data

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Research on Cross-Domain Heterogeneous Information Interaction system in Complex Environment Based on Blockchain Technology 1

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7th International Conference on Smart Computing and Communication, SmartCom 2022

作者： Ma, BaoQuan Cheng, YeJian Zhang, Ni Wang, Peng Lei, XuHua Huai, XiaoYong Li, JiaXin Jia, ShuJuan Wang, ChunXia National Computer System Engineering Research Institute of China Beijing102200 China School of Computer Science and Technology Xidian University Xi’an710071 China

ISBN: (数字)9783031281242

ISBN: (纸本)9783031281235

In the field of information interaction, when a project involves a large amount of cross-domain heterogeneous information, it is difficult to transmit and update the required information in a timely, accurate, reliable and safe manner in such a complex environment, thereby maintaining synchronization. The decentralization and immutability of blockchain technology provide new ideas for solving this problem. Therefore, this paper takes this as a starting point and proposes a cross-domain heterogeneous information exchange system based on blockchain, which calls smart contracts to realize data transmission and other functions. This paper states the design idea of the system, introduces the system software framework and network topology in detail, shows the flow chart of the system operation, and conducts simple software testing and verification. Finally, this work is summarized, and the development direction of future work is prospected, hoping to provide inspiration for the solution of such problems. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Smart contract

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RPRB-Net: A Sign Language Recognition Based on Multi-dimension Attentions

RPRB-Net: A Sign Language Recognition Based on Multi-dimensi...

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2023 International Conference on Machine Vision, Image Processing and Imaging Technology, MVIPIT 2023

作者： Yang, Tian Shen, Cong Wang, Xinyue Ma, Xiaoyu Tianjin University of Technology Engineering Research Center of Learning-Based Intelligent System Ministry of Education School of Computer Science and Engineering Tianjin China

ISBN: (纸本)9798350306545

Sign Language Recognition (SLR) is the process of translating sign language into text or speech, which can also be viewed as a communication and expression tool between deaf individuals and hearing people. SLR using deep neural network has undergone significant development over the last decade. In this study, we design a feature-enhanced SLR technique based on serval spaces. To aid the network learning features from channel and spatial dimensions, we inject various attention mechanisms into the feature extractor backbone. As a result, we named our approach ResNet + Pyramid-Split-Attention + Recurrent-Criss-Cross-Attention + BiLSTM Network (RPRB-Net). Besides, we employ the BiLSTM architecture to encode high-level representations in temporal sequence. The network is ultimately trained using an end-to-end CTC alignment strategy. Extensive trials show that RPRB-Net achieves WERs of 3.5% and 23.6% on the USTC and RWTH-2014 datasets, respectively. Besides, it implies that RPRB-Net significantly surpasses the cutting-edge SLR approaches. Additionally, numerous ablation experiments have confirmed the efficiency of configuration. © 2023 IEEE.

关键词： Audition

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Random Number Generator for Securing Data Exchange in Smart Factory: Recent Trends and Best Practices 3

Random Number Generator for Securing Data Exchange in Smart ...

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3rd International Conference on computer Technologies, ICCTech 2024

作者： Sama, Andi Meyliana Heryadi, Yaya Sahroni, Taufik Roni Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Information System Information System Department Jakarta11480 Indonesia BINUS Graduate Program-Doctor of Computer Science Jakarta Computer Science Department Jakarta11530 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Industrial Engineering Industrial Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350395419

IT/OT convergence in the form of a Cyber-Physical system (CPS) presents an opportunity to apply recent Information Technology (IT) advancements to Operational Technology (OT). The IT/OT convergence introduces cyber security threats for OT. The OT communication protocols, for example, have limited or no security capabilities for securing data exchange beyond basic authentication. The RNG (Random Number Generator) function is crucial in PLC for producing the encryption keys or the initial seed for security algorithms. The software-based PRNG (Pseudo RNG) is the most common approach for RNG in OT, instead of hardware-based RNG. This study provides a systematic literature review of the most recent evidence in digital transformation to secure data exchange in smart factories, within OT, or across OT and IT settings. It does this by looking at the PRNG on PLC and identifying the most recent trends and best practices. The findings include up-to-date data on author countries' distribution, published journals, research trends, industries, and industry types. The findings also address whether data flow is encrypted or shared in plaintext to ensure secure data transfer between IT and legacy OT environments. This paper concludes that while there is known RNG implementation in the actual embedded system in ICS, there is no evidence in the literature for using RNG in ICS networks for PLC implementation to secure data transfer with encryption. © 2024 IEEE.

关键词： Data transfer

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Trust Evaluation-based Machine Learning for WSNs 10

Trust Evaluation-based Machine Learning for WSNs

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17th INDIACom;2023 10th International Conference on Computing for Sustainable Global Development, INDIACom 2023

作者： Kumar, Aditya Singh, Karan Vats, Satvik School of Computer and System Sciences Jawaharlal Nehru University New Delhi India Computer Science and Engineering Graphic Era Hill University Dehradun India

ISBN: (纸本)9789380544472

Wireless sensor networks (WSNs) have many different applications in industries such as intrusion detection, healthcare, and environmental monitoring. To ensure their success, it is essential to establish trust among the sensor nodes to enhance trustworthiness, collaboration, and security. However, current trust management methods for large-scale WSNs have several drawbacks, including low dependability, high communication, and memory overhead, which make them ineffective. To address these issues, a new approach has been proposed, which uses trust evaluation-based machine learning for WSNs. This method involves determining trust attributes using a model and then creating a new algorithm based on machine learning to categorize and combine these trust features into a final trust value. This trust value can be used in decision-making to improve the effectiveness of WSNs. © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Principal component analysis

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FedMoS: Taming Client Drift in Federated Learning with Double Momentum and Adaptive Selection 42

FedMoS: Taming Client Drift in Federated Learning with Doubl...

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42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Wang, Xiong Chen, Yuxin Li, Yuqing Liao, Xiaofei Jin, Hai Li, Bo Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Wuhan China Wuhan University School of Cyber Science and Engineering Wuhan China Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong

ISBN: (纸本)9798350334142

Federated learning (FL) enables massive clients to collaboratively train a global model by aggregating their local updates without disclosing raw data. Communication has become one of the main bottlenecks that prolongs the training process, especially under large model variances due to skewed data distributions. Existing efforts mainly focus on either single momentum-based gradient descent, or random client selection for potential variance reduction, yet both often lead to poor model accuracy and system efficiency. In this paper, we propose FedMoS, a communication-efficient FL framework with coupled double momentum-based update and adaptive client selection, to jointly mitigate the intrinsic variance. Specifically, FedMoS maintains customized momentum buffers on both server and client sides, which track global and local update directions to alleviate the model discrepancy. Taking momentum results as input, we design an adaptive selection scheme to provide a proper client representation during FL aggregation. By optimally calibrating clients' selection probabilities, we can effectively reduce the sampling variance, while ensuring unbiased aggregation. Through a rigid analysis, we show that FedMoS can attain the theoretically optimal O(T - 2/3) convergence rate. Extensive experiments using real-world datasets further validate the superiority of FedMoS, with 58%-87% communication reduction for achieving the same target performance compared to state-of-the-art techniques. © 2023 IEEE.

关键词： Momentum

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FedRKG: A Privacy-Preserving Federated Recommendation Framework via Knowledge Graph Enhancement 18th

FedRKG: A Privacy-Preserving Federated Recommendation Framew...

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18th International Conference on Green, Pervasive, and Cloud Computing, GPC 2023

作者： Yao, Dezhong Liu, Tongtong Cao, Qi Jin, Hai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China School of Computing Science University of Glasgow Glasgow United Kingdom

ISBN: (纸本)9789819998951

Federated Learning (FL) has emerged as a promising approach for preserving data privacy in recommendation systems by training models locally. Recently, Graph Neural Networks (GNN) have gained popularity in recommendation tasks due to their ability to capture high-order interactions between users and items. However, privacy concerns prevent the global sharing of the entire user-item graph. To address this limitation, some methods create pseudo-interacted items or users in the graph to compensate for missing information for each client. Unfortunately, these methods introduce random noise and raise privacy concerns. In this paper, we propose FedRKG, a novel federated recommendation system, where a global knowledge graph (KG) is constructed and maintained on the server using publicly available item information, enabling higher-order user-item interactions. On the client side, a relation-aware GNN model leverages diverse KG relationships. To protect local interaction items and obscure gradients, we employ pseudo-labeling and Local Differential Privacy (LDP). Extensive experiments conducted on three real-world datasets demonstrate the competitive performance of our approach compared to centralized algorithms while ensuring privacy preservation. Moreover, FedRKG achieves an average accuracy improvement of 4% compared to existing federated learning baselines. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Recommender systems

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Design of Digital Twin Circuit Principle Experiment system Based on NCSLab 42

Design of Digital Twin Circuit Principle Experiment System B...

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42nd Chinese Control Conference, CCC 2023

作者： Li, Yu-Zhong Liu, Guo-Ping Yu, Yi School of Computer Science and Engineering Huizhou University Huizhou516007 China School of System Design and Intelligence Manufacture Southern University of Science and Technology Shenzhen518055 China

ISBN: (纸本)9789887581543

This paper is concerned with the requirements of current distance learning of circuit principle experiment of automation specialty, automatic fault detection of experimental equipment, automatic fault isolation, uninterrupted experiment in case of fault, and maintaining the number of available equipment. Specifically, based on the networked control system laboratory (NCSLab) architecture, digital twin, remote control technology and circuit design, aiming at the circuit experiment principle course, the digital twin are realized by Simulink, and a digital twin circuit principle experiment system(DT-CPES) is designed and implemented. The designed system shows that the system can realize the sharing of experimental equipment, the digital twin can predict, and can also verify with the actual measurement data of the circuit experiment. Through the digital twin fault isolation controller(DT-FIC), the fault diagnosis, fault isolation and replacement output of the experimental equipment can be realized. Therefore, the developed system reduces the overall risk and cost of installation and maintenance of large-scale circuit experiments, and provides fault-tolerant redundancy for the experimental system with low computational burden and high reliability. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Timing circuits

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