2022 18th International Conference on Mobility, Sensing and Networking (MSN)最新文献_第8页

Trusted-Committee- Based Secure and Scalable BFT Consensus for Consortium Blockchain 基于可信委员会的联盟区块链安全可扩展BFT共识

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/MSN57253.2022.00066

Liaoliao Feng, Y. Ding, Yusong Tan, Xiang Fu, Keming Wang, Junsheng Chang

引用次数: 0

A Quality-Aware Rendezvous Framework for Cognitive Radio Networks 认知无线网络的质量感知交会框架

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/MSN57253.2022.00019

Hai Liu, Lu Yu, C. Poon, Zhiyong Lin, Y. Leung, Xiaowen Chu

{"title":"A Quality-Aware Rendezvous Framework for Cognitive Radio Networks","authors":"Hai Liu, Lu Yu, C. Poon, Zhiyong Lin, Y. Leung, Xiaowen Chu","doi":"10.1109/MSN57253.2022.00019","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00019","url":null,"abstract":"In cognitive radio networks, rendezvous is a fundamental operation by which cognitive users establish communication links. Most of existing works were devoted to shortening the time-to-rendezvous (TTR) but paid little attention to qualities of the channels on which rendezvous is achieved. In fact, qualities of channels, such as resistance to primary users' activities, have a great effect on the rendezvous operation. If users achieve a rendezvous on a low-quality channel, the communication link is unstable and the communication performance is poor. In this case, re- rendezvous is required which results in considerable communication overhead and a large latency. In this paper, we first show that actual TTRs of existing rendezvous solutions increase by 65.40-104.38% if qualities of channels are not perfect. Then we propose a Quality-Aware Rendezvous Framework (QARF) that can be applied to any existing ren-dezvous algorithms to achieve rendezvous on high-quality channels. The basic idea of QARF is to expand the set of available channels by selectively duplicating high-quality channels. We prove that QARF can reduce the expected TTR of any rendezvous algorithm when the expanded ratio $lambda$ is smaller than the threshold $(-3+sqrt{1+4(frac{sigma}{mu})^{2}}) / 2$, where $mu$ and $sigma$, respectively, are the mean and the standard deviation of qualities of channels. We further prove that QARF can always reduce the expected TTR of Random algorithm by a factor of $1+(frac{sigma}{mu})^{2}$. Extensive experiments are conducted and the results show that QARF can significantly reduce the TTRs of the existing rendezvous algorithms by 10.50-51.05 % when qualities of channels are taken into account.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126374891","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

Energy Minimization for IRS-assisted UAV-empowered Wireless Communications 红外辅助无人机无线通信的能量最小化

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/MSN57253.2022.00162

Yangzhe Liao, Jiaying Liu, Yi Han, Quan Yu, Qingsong Ai, QUAN LIU, X. Zhai

{"title":"Energy Minimization for IRS-assisted UAV-empowered Wireless Communications","authors":"Yangzhe Liao, Jiaying Liu, Yi Han, Quan Yu, Qingsong Ai, QUAN LIU, X. Zhai","doi":"10.1109/MSN57253.2022.00162","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00162","url":null,"abstract":"Non-terrestrial wireless communications have evolved into a technology enabler for seamless connectivity and ubiquitous computing services in the beyond fifth-generation (B5G) and sixth-generation (6G) networks, aiming to provision reliable and energy efficient communications among aerial platforms and ground mobile users. This paper considers intelligent reflecting surface (IRS)-assisted unmanned aerial vehicle (UAV)-empowered wireless communication, which exploits both the high mobility of UAV and passive beamforming gain brought by IRS. The energy minimization of rotary-wing UAV is formulated by jointly considering numerous quality of service (QoS) constraints with intricately coupled variables. To tackle the formulated challenging problem, a heuristic algorithm is proposed. First, we decouple it into several subproblems. Moreover, we jointly investigate offloading decisions of Internet of Thing (IoT) devices by the proposed enhanced differential evolution algorithm. Then, minorization-maximization algorithm (MMA) is utilized to solve the optimization of IRS phase shift-vector. Moreover, ant colony optimization (ACO) algorithm is proposed to optimize UAV flight route indicator matrix. Numerical results validate the effectiveness of the proposed algorithm. The results show that the proposed solution can remarkably decrease UAV flight distance while improving the network energy efficiency in comparison with numerous advanced algorithms.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128108084","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

Intelligent rush repair of unmanned distribution network based on deep reinforcement learning 基于深度强化学习的无人配电网智能抢修

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/MSN57253.2022.00161

Yue Zhao, Yang Chuan, Shi Pu, Xuwen Han, Shiyu Xia, Yanqi Xie

{"title":"Intelligent rush repair of unmanned distribution network based on deep reinforcement learning","authors":"Yue Zhao, Yang Chuan, Shi Pu, Xuwen Han, Shiyu Xia, Yanqi Xie","doi":"10.1109/MSN57253.2022.00161","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00161","url":null,"abstract":"With the continuous expansion of China's power grid scale and the increasing number of power users year by year, it is necessary to ensure the normal power supply of users. When a power failure occurs, it is particularly critical whether the emergency repair task can be completed quickly and scientifically. In this paper, an intelligent repair model of “unmanned” distribution network based on deep reinforcement learning is proposed, which adopts speech recognition tech-nology and deep reinforcement learning algorithm to achieve the “unmanned” of the whole system. Users can transmit the emergency repair information to the voice recognition module of the power supply emergency repair center by voice, SMS and IMS, and the module will get the emergency repair position and the amount of emergency repair tasks. Then, the resource allocation module is used to learn the emergency repair resource allocation strategy online, and the intelligent control of emergency repair in distribution network is realized. To verify the proposed algorithm, it is compared with two typical allocation strategies under the same settings. The results of the experiments demonstrate that the method based on deep reinforcement learning performs better in terms of emergency repair delay and intelligent emergency repair of the power supply in distribution networks.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127204387","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

Measurement and Analysis: Does QUIC Outperform TCP? 测量与分析:QUIC是否优于TCP?

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/MSN57253.2022.00154

Xiang Qin, Xiaochou Chen, Wenju Huang, Yi Xie, Yixi Zhang

{"title":"Measurement and Analysis: Does QUIC Outperform TCP?","authors":"Xiang Qin, Xiaochou Chen, Wenju Huang, Yi Xie, Yixi Zhang","doi":"10.1109/MSN57253.2022.00154","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00154","url":null,"abstract":"Many web applications adopt Transfer Control Protocol (TCP) as the underlying protocol, where congestion control (CC) plays a vital role in reliable transmission. However, some TCP mechanisms cannot cope with the requirements of new applications and ever-increasing network traffic. Therefore, people have proposed Quick UDP Internet Connection (QUIC), an excellent potential alternative based on UDP, which introduces new features to improve transmission performance and is compatible with existing CC algorithms. This paper has conducted many experiments in the testbed and actual environments to measure and compare QUIC and TCP regarding communication quality, compatibility fairness, and user experience, while considering the impacts of three typical CC algorithms: NewReno, Cubic, and BBR. QUIC outperforms TCP in most experiments for web browsing and online video, but its performance is susceptible to CC algorithms and network conditions. For example, with the Cubic algorithm, QUIC enabling the 0-RTT feature can decrease the webpages loading time by 37.11% compared with TCP. Using the BBR algorithm, both QUIC and TCP achieve high throughput, slight fluctuation, and few delayed events when playing online videos. TCP with BBR provides better fairness, while QUIC with BBR is more robust in a network with high latency or packet loss.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132048758","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

Proactive Handover Mechanism for Blockage Avoidance in Indoor VLC Networks 室内VLC网络中避堵的主动切换机制

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/MSN57253.2022.00029

A. Vegni, P. Diamantoulakis

引用次数: 1

PeTrack: Smartphone-based Pedestrian Tracking in Underground Parking Lot PeTrack:基于智能手机的地下停车场行人跟踪

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/MSN57253.2022.00122

Xiaotong Ren, Shuli Zhu, Chuize Meng, Shan Jiang, X. Xiao, Dan Tao, Ruipeng Gao

引用次数: 0

UAV Visual Navigation System based on Digital Twin 基于数字孪生的无人机视觉导航系统

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/MSN57253.2022.00140

Jingsi Miao, Ping Zhang

{"title":"UAV Visual Navigation System based on Digital Twin","authors":"Jingsi Miao, Ping Zhang","doi":"10.1109/MSN57253.2022.00140","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00140","url":null,"abstract":"In recent years, many scholars have carried out researchs on UAV digital twin from various aspects. However, the research is still in the preliminary stage, and there are still some problems, such as incomplete data and model fusion, poor migration of algorithm policy, poor relation between virtual and physical space, and lack of extensibility of application scenarios. In order to explore the application potential of digital twin technology in UAV fields, this paper introduces digital twin into UAV monocular visual navigation. Therefore, this paper proposes a digital twin(DT)-based framework integrating with deep neural network, which consists of physical space, virtual space, twin data layer and application layer. Next, the multi-modal decision model with decoupling methods in application layer consisting of perception model and control model is built to explore the global optimal solution and control the behaviors of UAV. Finally, the digital twin system and decision model are verified in virtual space and physical space respectively. The results shows that the UAV visual navigation system based on digital twin reduces the cost of application, algorithm development and deployment, and improves the migration ability of navigation policy. Compared with the baselines, the proposed decision model has the best navigation performance in both virtual space and physical space. Compared with the navigation policy without the decoupling method, the performance index is improved by about 8.6% in virtual space and 2.7 times in physical space.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"74 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116283277","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

Characterizing Energy Sources in Outdoor Wireless Sensor Networks 户外无线传感器网络中能量的表征

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/MSN57253.2022.00028

R. Hartung, J. Käberich, Christian Bunzeck, Lars C. Wolf

引用次数: 0

Binary Neural Network with P4 on Programmable Data Plane 基于可编程数据平面的P4二进制神经网络

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/MSN57253.2022.00155

Junming Luo, Waixi Liu, Miaoquan Tan, Haosen Chen

{"title":"Binary Neural Network with P4 on Programmable Data Plane","authors":"Junming Luo, Waixi Liu, Miaoquan Tan, Haosen Chen","doi":"10.1109/MSN57253.2022.00155","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00155","url":null,"abstract":"Deploying machine learning (ML) on the programmable data plane (PDP) has some unique advantages, such as quickly responding to network dynamics. However, compared to demands of ML, PDP have limited operations, computing and memory resources. Thus, some works only deploy simple traditional ML approaches (e.g., decision tree, K-means) on PDP, but their performance is not satisfactory. In this article, we propose P4-BNN (Binary Neural Network based on P4), which uses P4 to completely executes binary neural network on PDP. P4-BNN addresses some challenges. First, in order to use shift and simple integer arithmetic operations to replace multiplication, P4-BNN proposes a tailor-made data structure. Second, we use an equivalent replacement programming method to support matrix operation required by ML. Third, we propose a normalization method in PDP which needn't floating-point operations. Fourth, by using register storing the model parameters, the weights of P4-BNN model can be updated without interrupting the P4 program running. Finally, as two use-cases, we deploy P4-BNN on a Netronome SmartNIC (Agilio CX 2x10GbE) to achieve flow classification and anomaly detection. Compared to the N3IC, decision tree and K-means, the accuracy of P4-BNN has 1.7%, 3.4% and 47.7% improvement respectively.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121096754","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