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检索条件"任意字段=23rd International Conference on Control Systems and Computer Science Technologies, CSCS 2021"

共 285 条记录，以下是121-130 订阅

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Semantic-Based Heterogeneous controller Collaboration for Space-Terrestrial Integrated Networks 23

Semantic-Based Heterogeneous Controller Collaboration for Sp...

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23rd IEEE international conference on High Performance Computing and Communications, 7th IEEE international conference on Data science and systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Bao, Yaru Tang, Feilong Li, Xu Chen, Long Liu, Jiacheng Yang, Yanqin Xu, Wenchao Cao, Lijun Han, Ping Shanghai Jiao Tong University Department of Computer Science & Engineering China School of Data Science & Engineering East China Normal University China School of Communication & Electronic Engineering East China Normal University China Innovation Resource Center Kedacom Co. Ltd China The Sci-Tech Information Office of Xuzhou Public Security Bureau China

ISBN: (纸本)9781665494571

In heterogeneous SDN networks, controllers deploying different protocols need to cooperate with each other and establish a global network view that can be passed to the network applications for unified management and end-to-end decision-making. Unfortunately, there is no standard northbound interface protocol to integrate heterogeneous SDN controllers. To address this issue in this paper, we propose an approach to find the mapping among controller ontologies in the SDN network with heterogeneous controllers in this paper. We regard these controller ontologies as a solution for discovering similar elements between local ontologies and global ontology. By mapping controller ontologies in the heterogeneous network together, we can form the complete network view to achieve centralized management. The idea behind the approach is to use ontology to represent the conceptual data of various heterogeneous controllers and then map similar semantic data together to form a consistent, global network knowledge. Evaluation results show that our approach has better accuracy than other algorithms and has an acceptable execution time. © 2021 IEEE.

关键词： Knowledge engineering Satellites Protocols Semantics Decision making Collaboration Ontologies

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A Fine-grained volley gesture recognition method with Direction Independence 23

A Fine-grained volley gesture recognition method with Direct...

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作者： Hao, Zhanjun Liu, Gaoyuan Dang, Xiaochao Zhang, Daiyang Bai, Yanhong Xu, Hongwen Northwest Normal University School of Computer Science and Engineering LanZhou China

ISBN: (纸本)9781665494571

The development of wireless sensing technology makes it possible to control various IoT devices with gestures. In the current severe international epidemic situation, the use of non-contact gesture recognition methods can greatly reduce direct or indirect contact between people and effectively curb the spread of the virus. However, since the direction, position, and motion range of each person's gesture are different, it brings great challenges to the accurate recognition of gestures. To solve this problem, this paper proposes a direction-independent fine-grained volley gesture recognition method CSI-VGR based on Wi-Fi signal sensing technology. CSI-VGR first converts the CSI signal of a gesture into a Doppler shift. In particular, CSI-VGR uses a temporal convolutional network (TCN) to segment the gesture action and extract the features of each gesture. Finally, the Echo State Network (ESN) is introduced, and the gesture feature is input to obtain the classification result of the gesture. This paper verifies the performance of CSI-VGR in multiple dimensions in two real scenarios. Experimental results show that the gesture recognition accuracy of the CSI-VGR method can reach 96.3%, and it shows satisfactory robustness in both scenarios. © 2021 IEEE.

关键词： Wireless communication Wireless sensor networks Smoothing methods Convolution Gesture recognition Interference Feature extraction

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A Spatiotemporal Analysis of Age of Information at V2X-enabled Intersection 23

A Spatiotemporal Analysis of Age of Information at V2X-enabl...

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作者： Wang, Yaying Tan, Guoping Zhou, Siyuan Yang, Dengsong Ni, Baili Hohai University Key Laboratory of Water Big Data Technology of Ministry of Water Resources Nanjing China College of Computer and Information Hohai University Nanjing China Jiangsu Intelligent Transportation and Intelligent Driving Research Institute Nanjing China Jiangsu Expressway Company Limited China

ISBN: (纸本)9781665494571

Ensuring the freshness of information is of importance to autonomous vehicles at vehicle-to-everything (V2X)-enabled intersection. In this paper we theoretically investigate the Age of information (AoI) at V2X-enabled suburban intersections and urban intersections. Specifically, we model the locations of connected vehicles by using stochastic geometry and consider a last-come first-serve discipline with preemption. Then we analyze the moments and distribution of the conditional successful probability and the conditional average AoI. Finally, we obtain the moments and the distribution of conditional average AoI. The accuracy of theoretical derivation is verified via simulations. Our numerical results show the influence of different parameters on the average AoI and the theoretical analysis provides a useful guideline for further system design. © 2021 IEEE.

关键词： Transmitters Smart cities Roads Stochastic processes Receivers Information age Spatiotemporal phenomena

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Improving Indoor Positioning systems with UWB and Filtering Techniques: A ComparativeAnalysis 23

Improving Indoor Positioning Systems with UWB and Filtering ...

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23rd international conference on control, Automation and systems, ICCAS 2023

作者： Rahul Ranjan, First A. Younsik Jung, Second B. Donggyu, Shin Kim, Third. Sanghyun Kim, Chang-Hyun Lee, Seungjae Kye, Joongeup Intelligent Robot Research Institute Sun Moon University Department of Computer Engineering and Electronics Convergence Asan31460 Korea Republic of Intelligent Robot Research Institute Sun Moon University Department of Computer Science and Engineering Asan31460 Korea Republic of Kyung Hee University Department of Mechanical Engineering Suwon17104 Korea Republic of Korea Institute of Machinery & Materials Daejeon34103 Korea Republic of Intelligent Robot Research Institute Sun Moon University Department of Mechanical Engineering Asan31460 Korea Republic of

ISBN: (纸本)9788993215274

In today's world, indoor positioning systems(IPS) have become a fascinating research area. Accurate positioning of mobile robots in indoor environments remains challenging due to various positioning techniques and the complexities associated with dynamic environments, dense obstacles, and different material types. Indoor localization systems face challenges in reducing noise and enhancing accuracy. In this paper, an Ultra-Wideband(UWB) based localization system is under test to evaluate the efficiency of the measurement using two different methods, Low-Pass Filter(LPF) and Kalman Filter(KF), on Robot Operating System(ROS) platform. This study aims to assess and compare the effectiveness of the proposed methods in reducing noise and improving the accuracy of indoor localization systems. A set of position data was recorded in the lab environment. The proposed Filtered is applied and compared with target trajectory paths. The findings of this research contribute to the development of robust and reliable indoor localization systems crucial for various applications, including mobile robotics, automation, and human-computer interaction. © 2023 ICROS.

关键词： Kalman filters

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Blockchain-Assisted Privacy-Preserving Public Auditing Scheme for Cloud Storage systems 1

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23rd international conference on Algorithms and Architectures for Parallel Processing (ICA3PP)

作者： Xiang, Wenyu Zhao, Jie Huang, Hejiao Zhang, Xiaojun Jiang, Zoe Lin He, Daojing Harbin Inst Technol Sch Comp Sci & Technol Shenzhen 518055 Guangdong Peoples R China Southwest Petr Univ Sch Comp Sci Res Ctr Cyber Secur Chengdu 610500 Peoples R China

ISBN: (数字)9789819708017

ISBN: (纸本)9789819708000;9789819708017

Public auditing mechanism can delegate a third-party auditor (TPA) to check the remote data integrity on behalf of data owners. However, the TPA, as an idealized and benefit-oriented entity, may not provide correct auditing results on time. To date, a large number of public auditing schemes utilize the booming blockchain technique to resist dishonest TPA, but most of them are vulnerable to malicious miners who attempt to manipulate the randomness of auditing challenge generation. In this paper, we propose a novel Blockchain-assisted Privacy-preserving Public Auditing scheme, named BPPA. The BPPA scheme utilizes a smart contract deployed on the Ethereum blockchain to replace the TPA. To eliminate the impact of malicious miners, the smart contract employs unpredictable hash values of the nearest Ethereum blocks to generate the index locators. These locators segmentally produce index subsets of challenged data blocks, ensuring the unpredictability of auditing challenge messages. Meanwhile, BPPA achieves conditional identity anonymity for data owners through the employment of identity-based public key cryptography and key exchange technique. We prove the security of our scheme based on the computational Diffie-Hellman assumption and the discrete logarithm assumption. Furthermore, we analyze the performance from theoretical and experimental aspects, and the evaluation results demonstrate that our auditing scheme is effective and efficient.

关键词： Cloud storage system Remote data integrity Ethereum blockchain Malicious miner Conditional identity anonymity

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HANA-MES: A HMI-awared Manufacturing Execution System 23

HANA-MES: A HMI-awared Manufacturing Execution System

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作者： Chen, Jingjing Wu, Hequn Li, Yafei Wu, Xiaoxin Zhao, Yueqiang Shi, Yao Tang, Songjia Shi, Yulun Chen, Hangyi Fudan University School of Economics Shanghai China Zhejiang Police College Department of Public Teaching Hangzhou China Zhengzhou University School of Information Engineering Zhengzhou China Zhejiang University School of Medicine The First Affiliated Hospital Hangzhou China School of Finance and Business Shanghai Normal University Shanghai China Zhejiang University School of Medicine Affiliated Hangzhou First People's Hospital Plastic and Aesthetic Surgery Department Hangzhou China Sunyard System Engineering Co. Ltd Hangzhou China Huzhou Branch of China United Network Communication Co. Ltd Huzhou China

ISBN: (纸本)9781665494571

With the rapid development of technologies such as cyber-physical systems, big data, cloud computing and industrial wireless networks, the concept of Industry 4.0 is gradually gaining popularity in the industrial world, in which, manufacturing Execution System (MES) plays an important role in connecting the high-level functions of the enterprise and the production/manufacturing operations. The lack of immediate awareness of the state of the manufacturing system and the human-computer interaction methods with it is the main obstacle to build this intelligent manufacturing environment. In this paper, we propose a data-centric, human machine interaction-aware MES solution: HANA-MES, to visually sense the system (global/local) state to support the capabilities of smart scheduling, dynamic scheduling, precision management of production processes and preventive maintenance of equipment in smart manufacturing environments. We present the HMI-aware design, and the detailed functional implementation of HANA-MES. In addition, the usage data are collected by distributing questionnaires and analyzed to verify the system usability and effectiveness of HMI-aware design. The operators and managers of Zhejiang Yongsheng Co., Ltd, both reported positive feedback on adopting the new MES in their factories. The statistical analysis during the 2018-2020 shows that the new system could obviously save the time and improve the production efficiency. © 2021 IEEE.

关键词： Human computer interaction Job shop scheduling Statistical analysis Wireless networks Dynamic scheduling Production facilities Usability

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DMF-MPC: A Dual-Stage and Multi-Step Forecasting Model Based Cooling System control Method for Data Center Energy Cost Minimization 23

DMF-MPC: A Dual-Stage and Multi-Step Forecasting Model Based...

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作者： He, Xinrui Chen, Weiduo Dong, Xiaoshe Wang, Qiang Liu, Jialin Dong, Fan Su, Yuanqi School of Computer Science and Technology of Xi'an Jiaotong University Xi'an Jiaotong University Xi'an China

ISBN: (纸本)9781665494571

Nowadays, surveys show that the cooling system accounts for 30% of the energy consumption of data centers. The challenge of designing an effective cooling control system to minimize data center energy consumption cost as much as feasible while maintaining normal operation is a pressing one to address. The traditional cooling control method produces excessive cooling energy consumption, which causes a large amount of energy waste and economic expenses;Moreover, the existing Model Predictive control (MPC) method based on the physical model has high modeling difficulty and model migration cost, and can only provide short-term control strategy. In this paper, we propose an MPC method based on a dual-stage and multi-step forecasting model (DMF-MPC), which can forecast the cooling system energy consumption in data centers accurately and provide a cost-saving control strategy of the cooling system for the next 24 hours on a combination of the peak-valley time-of-use (TOU) electricity price. We firstly propose a dual-stage and multi-step forecasting model (DMFM), a pure data-driven deep learning model, which adopts the historical server features of data centers, future weather factors, and cooling control to forecast the cooling system energy consumption for the multiple future periods, also a multi-step iterative training method is proposed in the training process to reduce the multi-step forecasting errors. In the control part of DMF-MPC, we introduce an optimal control model for the data center cooling system based on DMFM. The cost-saving control strategy for the next 24 hours under the peak-valley TOU electricity price standard can be obtained by solving the model through optimization algorithms. Finally, the effectiveness of the method is verified by validating DMF-MPC in a real campus high-performance computing (HPC) data center located in China. Our method achieves a 15%-25% cost reduction in the experiment. © 2021 IEEE.

关键词： Training Data centers Energy consumption Costs Cooling Computational modeling Weather forecasting

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Lane-Level Traffic Flow Prediction Based on Dynamic Graph Generation 23

Lane-Level Traffic Flow Prediction Based on Dynamic Graph Ge...

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作者： Wang, Lingyun Shen, Guojiang Yu, Kaifeng Ji, Zhanhao Kong, Xiangjie College of Computer Science and Technology Zhejiang University of Technology Hangzhou China

ISBN: (纸本)9781665494571

The Intelligent Transportation System (ITS) plays a critical role in the development of smart cities, and the traffic control capability of ITS requires accurate traffic flow prediction as the footstone. Due to the neglect of the dissimilarities between lanes, existing traffic flow prediction methods like T-GCN are intractable to capture the dynamic changes of traffic flow direction, lane relationship, etc. Therefore, studies are shifting their concern to lane-level traffic flow prediction for tackling with more complicated scenarios. However, how to handle temporal-spatial correlation and model heterogeneous data effectively is still a challenge. In this paper, we propose a heterogeneous graph convolution model based on dynamic graph generation to address the issue. The model consists of three components. The internal graph convolution network captures the real-time spatial dependency between lanes in terms of generated dynamic graphs. The external heterogeneous data fusion network comprehensively considers other parameters such as lane speed, lane occupancy, and weather conditions. The codec neural network utilizes a temporal attention mechanism to capture the deep temporal dependency. Substantial experiments based on two real-world datasets indicate that the proposed heterogeneous graph convolution model can improve prediction accuracy. © 2021 IEEE.

关键词： Codecs Convolution Smart cities Roads Road side unit Transfer learning Data integration

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On Performance of Cooperative V2X Communication with Vehicular Platoon systems 23

On Performance of Cooperative V2X Communication with Vehicul...

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作者： Zhou, Siyuan Wu, Qianqian Tan, Guoping Yang, Dengsong Ni, Baili College of Computer and Information Hohai University Nanjing China Jiangsu Intelligent Transportation and Intelligent Driving Research Institute Nanjing China Hohai University Key Laboratory of Water Big Data Technology of Ministry of Water Resources Nanjing China Jiangsu Expressway Company Limited China

ISBN: (纸本)9781665494571

With the development of intelligent traffic system, it is critical to use vehicle platooning to improve the safety and efficiency of vehicles. Vehicle-to-everything (V2X) communication technology is the key to guarantee the stability of platooning and cooperative communication technique can be leveraged to improve the communication coverage. In this paper, we first constructed an Amplify-and-forward (AF) relay communication network for vehicular platooning where the base station (BS) or the road side unit (RSU) can be selected as the relay node. Then, we carried out the performance analysis of the communication success probability by using stochastic geometry. The distribution of the locations of vehicles and RSUs is modeled by Poisson line process (PLP) and the spatial layout of BSs is modeled by a 2D Poisson point process (PPP). The BS or RSU is selected as the relay node according to their location. By deriving the association probability to BS or RSU, we derive the analytical solution of the success probability of the system. Simulation results verify our analysis and reveal the impact of the system parameters on the relay network performance. © 2021 IEEE.

关键词： Smart cities Simulation Roads Vehicle driving Stochastic processes Stability analysis Topology

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Migrating Deep Learning Data and Applications among Kubernetes Edge Nodes 23

Migrating Deep Learning Data and Applications among Kubernet...

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作者： Mangkhangcharoen, Suchanat Haga, Jason Rattanatamrong, Prapaporn Thammasat University Department of Computer Science Pathum Thani Thailand National Institute of Advanced Industrial Science and Technology Tsukuba Japan

ISBN: (纸本)9781665494571

Many current IoT applications deployed at the edge use deep learning (DL) in their real-time processing and analytics. Not only inference but also training is moving to edge devices. DL application and dataset migration among these devices are mandatory for scenarios like node failure, user mobility or when nodes need to collaborate (e.g., distributed training). Container technologies and Kubernetes (K8s) are being increasingly adopted to manage infrastructure at the edge. Unfortunately, there is no built-in mechanism in K8s to support migration of stateful containers between its cluster nodes. The K8s cluster's master node generally launches a new fresh container in another node to replace the failed one. While there is an existing mechanism for migrating a Pod between K8s nodes, there is no past work investigating the migration of DL datasets and containerized DL applications among K8s cluster nodes. In this paper, we present our 1) comprehensive study on the effectiveness and limitations of existing checkpointing mechanisms for containerized DL applications and 2) our comparative performance study of several approaches in migrating DL datasets and applications in a K8s cluster. Our results show that migrating states of DL applications and restoring them from their previous states enables faster recovery (reducing training time by 10 to 73 percent) than re-running these models from the beginning regardless of the percentage of epochs that have completed. Additionally, our experimental results show that transferring a dataset between K8s workers using the K8s persistent volume with kubectl cp is generally suitable and efficient. However, when network latency is high, using our customized middleware with a feedback controller to migrate data in parallel can speed up total migration time compared to the K8s's persistent volume approach alone. © 2021 IEEE.

关键词： Training Deep learning Checkpointing computers Containers Real-time systems Internet of Things

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