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2020 16th International Conference on Mobility, Sensing and Networking (MSN)最新文献

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Research on visualization planning method of distribution network based on graphical model integration 基于图形模型集成的配电网可视化规划方法研究
2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00123
Huang He, Zhou Xian, Guo Liang, Chang Hao, Ma Ning
{"title":"Research on visualization planning method of distribution network based on graphical model integration","authors":"Huang He, Zhou Xian, Guo Liang, Chang Hao, Ma Ning","doi":"10.1109/MSN50589.2020.00123","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00123","url":null,"abstract":"High efficient video coding (HEVC) is a new video coding compression standard. HEVC adopts context-based adaptive binary arithmetic coding (CABAC) as the entropy coding scheme. In this paper, the overall architecture and efficiency of the main frequency are improved by the optimization of the input and output modules and the module optimization of the arithmetic coding CABAC hardware structure. In terms of input module optimization, four-level buffer input and residual coefficient transmission optimization are adopted; in terms of arithmetic coding module optimization, context model index pre-reading, pre-normalization look-up table and in-line serial stream output design are adopted so as to improve the overall efficiency of the architecture and the main frequency, reduce resource consumption, and achieve a high-frequency hardware architecture of the efficient coding pipeline. The combined results show that the pipeline can operate at 370MHz with 43.49K gates aiming at 90nm process. The processing rate and throughput can support real-time encoding of 1080P video under the general test conditions of the HEVC standard of 30 frames per second.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122901625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Gesture Recognition System Based on Neural Networks by Using COTS RFID Tag Array 基于COTS RFID标签阵列的神经网络手势识别系统
2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00115
Jiaying Wu, Chuyu Wang, Lei Xie
{"title":"Gesture Recognition System Based on Neural Networks by Using COTS RFID Tag Array","authors":"Jiaying Wu, Chuyu Wang, Lei Xie","doi":"10.1109/MSN50589.2020.00115","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00115","url":null,"abstract":"Nowadays, gesture recognition plays a more and more important role in human-computer interaction. In this regard, contact sensors or computer vision have made some progress, but they also have shortcomings in portability or privacy. In this work, we propose a gesture recognition system which uses RFID tag array and neural networks to recognize gestures. By using an RFID tag array, we can obtain gesture information in a non-contact, non-infringing manner. By combining CNN and LSTM as CNN-LSTM, we can focus on both spatial and temporal features and get better performance. Experiments show that the accuracy of the system on the test set is 92.17%, and it performs well in recognizing different gestures of different users at different speeds.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123621371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Demo Abstract: Vision-aided 3D Human Pose Estimation with RFID 摘要:基于RFID的视觉辅助三维人体姿态估计
2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00104
Chao Yang, Xuyu Wang, S. Mao
{"title":"Demo Abstract: Vision-aided 3D Human Pose Estimation with RFID","authors":"Chao Yang, Xuyu Wang, S. Mao","doi":"10.1109/MSN50589.2020.00104","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00104","url":null,"abstract":"Radio Frequency (RF) based human pose estimation techniques have been proposed to generate human pose without using a camera, so people will no longer worry about their privacy. Compared with other RF sensing based systems, Radio Frequency Identification (RFID) provides a promising solution for RF based human pose estimation. RFID tags can be used as wearable sensors because of their small size. The interference caused by the multipath effect is much smaller in the RFID system. The cost of RFID systems is also lower than the advanced radar based systems such as FMCW radar. Thus, we propose the RFID-Pose system for tracking the movements of multiple human limbs in realtime [1]. In the proposed system, RFID tags are attached to the target human joints. The movement of the tags are captured by the phase variations in the responses from each tag. The human pose is reconstructed by estimating rotation angles from RFID data and the initial human skeleton. The vision data will not be needed anymore in the testing phase, so the user’s privacy can be well protected.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121517249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Virtual Machine Security Migration Strategy Based on the Edge Computing Environment 基于边缘计算环境的虚拟机安全迁移策略
2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00137
Ruizhong Du, Wangkai He, Junfeng Tian
{"title":"Virtual Machine Security Migration Strategy Based on the Edge Computing Environment","authors":"Ruizhong Du, Wangkai He, Junfeng Tian","doi":"10.1109/MSN50589.2020.00137","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00137","url":null,"abstract":"For mobile edge computing, the migration time between traditional cloud servers and edge devices is long, and there are security issues such as man-in-the-middle attacks in the process. In this regard, a migration scheme centered on edge nodes is proposed. The edge node is closer to the edge device, which can shorten the migration time. The solution uses the Transport Layer Security (TLS) protocol for key exchange to establish a session-secure communication channel, and virtual machine migration between edge devices is carried out in the channel by dynamic migration. The simulation results show that compared with that of other schemes, the migration time of the virtual machines is shortened. Security analysis shows that this solution can not only meet the requirements of data confidentiality and integrity but also resist man-in-the-middle attacks.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130042264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Privacy-Preserving Techniques for Protecting Large-Scale Data of Cyber-Physical Systems 网络物理系统大规模数据保护的隐私保护技术
2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00121
Marwa Keshk, Nour Moustafa, E. Sitnikova, B. Turnbull, Dinusha Vatsalan
{"title":"Privacy-Preserving Techniques for Protecting Large-Scale Data of Cyber-Physical Systems","authors":"Marwa Keshk, Nour Moustafa, E. Sitnikova, B. Turnbull, Dinusha Vatsalan","doi":"10.1109/MSN50589.2020.00121","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00121","url":null,"abstract":"As Cyber-Physical Systems (CPSs), such as power and gas networks, generate heterogeneous and large-scale data sources from devices and networks, they need efficient privacy-preserving techniques to protect data and systems from cyber attacks. To safeguard CPSs from potential cyber threats, it is vital to identify vulnerabilities of CPSs’ components to prevent Advanced Persistent Threats (APTs) and protect their generated data using privacy-preserving techniques. This paper aims to review the current state of privacy-preserving techniques for protecting CPSs and their networks against cyber attacks. Concepts of Privacy preservation and CPSs are discussed, illustrating CPSs’ components and how they could be hacked using cyber and physical hacking scenarios. Then, types of privacy preservation, including perturbation, authentication, machine learning (ML), cryptography and blockchain, are discussed to demonstrate how they would be applied to protect the original data in CPSs and their networks. Finally, we explain existing challenges, solutions and future research directions of privacy preservation in CPSs.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"241 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130759180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
An Online Pricing Strategy of EV Charging and Data Caching in Highway Service Stations 高速公路服务站电动汽车充电在线定价策略及数据缓存
2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00028
Zhou Su, Tianxin Lin, Qichao Xu, Nan Chen, Shui Yu, Song Guo
{"title":"An Online Pricing Strategy of EV Charging and Data Caching in Highway Service Stations","authors":"Zhou Su, Tianxin Lin, Qichao Xu, Nan Chen, Shui Yu, Song Guo","doi":"10.1109/MSN50589.2020.00028","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00028","url":null,"abstract":"With the technical advancement of transportation electrification and Internet of vehicle, an increasing number of electric vehicles (EVs) and related infrastructures (e.g., service stations with both charging and communication services) are deployed in the intelligent highway systems. Not only can EVs enter the service station areas for charging, but they can also upload/download cached data at service stations to access multiple networking services. However, as EVs are operated individually with their unique travelling patterns, questions arise as how to incent EVs so that both energy and communication resources are optimally allocated. In this paper, we propose an online pricing mechanism of EV charging and data caching for service stations along the highway. First, we design an online reservation system at each EV to decide the best service station to park when the EV enters the highway. Furthermore, based on the variant power system status, an online pricing mechanism is devised to update the charging and caching price based on Q-learning, by which EVs can be motivated to arrive at the designated station for services. Finally, simulation results validate the effectiveness of the proposed scheme in improving the station’s utility.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"162 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123328721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
AI2OT 2020 Workshop aiot 2020研讨会
2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/msn50589.2020.00010
{"title":"AI2OT 2020 Workshop","authors":"","doi":"10.1109/msn50589.2020.00010","DOIUrl":"https://doi.org/10.1109/msn50589.2020.00010","url":null,"abstract":"","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115979149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Researches on Intelligent Traffic Signal Control Based on Deep Reinforcement Learning 基于深度强化学习的智能交通信号控制研究
2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00124
Juan Luo, Xinyu Li, Yanliu Zheng
{"title":"Researches on Intelligent Traffic Signal Control Based on Deep Reinforcement Learning","authors":"Juan Luo, Xinyu Li, Yanliu Zheng","doi":"10.1109/MSN50589.2020.00124","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00124","url":null,"abstract":"The rapidly growing traffic flow exceeds the capacity of the existing infrastructure. It will cause traffic congestion and increase travel time and carbon emissions. Intelligent traffic signal control is a significant element in intelligent transportation system. In order to improve the efficiency of intelligent traffic signal control, the traffic information needs to be collected and processed in real-time. In this paper, we propose a deep reinforcement learning model for traffic signal control. In this model, intersections are divided into several grids of different sizes, which represents the complex traffic state. The switching of traffic signals are defined as actions, and the weighted sum of various indicators reflecting traffic conditions is defined as rewards. The whole process is modeled as Markov Decision Process (MDP), and Convolutional Neural Network (CNN) is used to map the states to rewards. We evaluated the efficiency of the model through Simulation of Urban Mobility (SUMO), and the simulation results proved the efficiency of the model.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128090571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
A Geometry-based Non-stationary Wideband MIMO Channel Model and Correlation Analysis for Vehicular Communication Systems 基于几何的车载通信系统非平稳宽带MIMO信道模型及相关分析
2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00084
Suqin Pang, Fan Bai, Di Zhang, Zheng Wen, Takuro Sato
{"title":"A Geometry-based Non-stationary Wideband MIMO Channel Model and Correlation Analysis for Vehicular Communication Systems","authors":"Suqin Pang, Fan Bai, Di Zhang, Zheng Wen, Takuro Sato","doi":"10.1109/MSN50589.2020.00084","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00084","url":null,"abstract":"In this paper, we propose a novel two-dimensional (2D) non-stationary geometry-based stochastic model (GBSM) for wideband multiple-input multiple-output (MIMO) base station-to-vehicle (B2V) channels. The proposed model combines one-ring and multiple ellipses with time-variant parameters, which can capture the channel non-stationary characteristics more precisely. The corresponding stochastic simulation model is then developed with finite number of effective scatterers. In addition, the birth-death process is applied to determine the number of ellipses in the proposed model at different time instants. Afterwards, the time-variant parameters and time-variant space cross-correlation functions (CCFs) are derived and analyzed. The impact of different parameters on the space CCFs such as vehicle traffic density (VTD) is investigated. Numerical results illustrate that the simulation model has great agreement with the reference model at different time instants, which indicates the correctness of our derivations.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130192174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Real-time Task Offloading for Data and Computation Intensive Services in Vehicular Fog Computing Environments 车载雾计算环境下数据和计算密集型业务的实时任务卸载
2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00066
Chunhui Liu, Kai Liu, Xincao Xu, Hualing Ren, Feiyu Jin, Songtao Guo
{"title":"Real-time Task Offloading for Data and Computation Intensive Services in Vehicular Fog Computing Environments","authors":"Chunhui Liu, Kai Liu, Xincao Xu, Hualing Ren, Feiyu Jin, Songtao Guo","doi":"10.1109/MSN50589.2020.00066","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00066","url":null,"abstract":"Recent advances in wireless communication, sensing, and computing technologies have paved the way for the development of a new era of Internet of Vehicles (IoV). Nevertheless, it is challenging to process data and computation intensive tasks with strict time constraints due to heterogeneous communication, storage, and computation capacities of IoV network nodes, spotty wireless connections in vehicles and infrastructures, unevenly distributed workload, and high vehicles mobility. In this paper, we propose a two-layer vehicular fog computing (VFC) architecture to explore the synergistic effect of the cloud, the fog nodes, and the terminals on processing data and computation intensive IoV tasks. Then, we formulate the real-time task offloading model, aiming at maximizing the task service ratio. Further, considering the dynamic requirements and resource constraints, we propose a real-time task offloading algorithm to adaptively categorize all tasks into four types, and then cooperatively offload them. Finally, we build the simulation model and give a comprehensive performance evaluation, which validates the performance of the proposed method.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133672204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
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