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第34届中国控制与决策会议

作者： Wenbo Chang Baoqi Huang Bing Jia Wuyungerile Li Gang Xu Engineering Research Center of Ecological Big Data Ministry of Education Inner Mongolia A.R.Key Laboratory of Wireless Networking and Mobile Computing College of Computer Science Inner Mongolia University

Online public transit ridership flow information is helpful to improve the service quality of urban public transportation and travel experience of *** WiFi sensing collects WiFi probe requests sent by mobile devices in a non-intrusive manner,and can thus be used to monitor ridership *** with the existing methods based on manual configurations or video surveillance,passive WiFi sensing based methods demonstrate the advantages of small interference,large coverage,low cost and simple *** recent years,researchers proposed some offline methods based on passive WiFi sensing,but offering online information is still *** paper develops a public transit ridership flow monitoring system using customized WiFi sniffers,and proposes an algorithm to implement online public transit ridership flow ***,the proposed algorithm uses the bidirectional long short-term memory neural network(BiLSTM) to capture the bidirectional time series features contained in WiFi sensing data,and further integrates the attention mechanism to focus on the critical features in relation to *** experimental results,carried out on four bus routes in Hohhot,China,show that the RMSE and MAE errors of the proposed algorithm are 3.96 and 3.1,respectively,which are better than those of the other 7 commonly used online ***,the accuracy of the proposed algorithm is 5% lower than that of the corresponding offline algorithm,but it is evident that our online algorithm will stimulate more practical applications.

关键词： Passive WiFi sensing Online Public transit ridership flow Attention mechanism BiLSTM

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Admission Control with Latency Considerations for 5G mobile Edge computing

Admission Control with Latency Considerations for 5G Mobile ...

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IEEE International Symposium on World of wireless mobile and Multimedia Networks (WoWMoM)

作者： Ye Zhang Wuyungerile Li Winston K.G. Seah Inner Mongolia Key Lab. of Wireless Networking & Mobile Computing Engineering Research Center of Ecological Big Data Ministry of Education School of Computer Science Inner Mongolia University Hohhot China Wireless Networks Research Group School of Engineering and Computer Science Victoria University of Wellington Wellington New Zealand

The fifth generation (5G) mobile network is a new generation of broadband mobile communication technology with the potential to address the increasing demands of new user services and applications that have stringent low latency and high bandwidth requirements. Besides the enhanced mobile broadband (eMBB) which is an evolution of broadband services from previous generations, the ultra reliable low latency communication (URLLC) service comes with stringent delay requirements that are needed to support new applications like autonomous vehicles, augmented/virtual reality, etc. mobile or multiple access edge computing (MEC) emerged to provide services and computing resources for users at the network edge to provide faster access speeds and lower end-to-end delays. To better meet user needs and maximize resource utilization, network resources need to be allocated and managed efficiently. Admission control for user requests is one of the methods used that can effectively prevent network congestion, thereby improving the overall performance of the system. In this paper, we propose a RED-based Admission Control with Latency Considerations (REDAL) algorithm for user admission control that aims to increase throughput, meet users’ delay requirements and reduce packet discard rate. By explicitly accounting for user traffic delay constraints and bandwidth requirements, we are able to meet the strict delay constraints of URLLC traffic while meeting the bandwidth requirements of eMBB traffic. We validate our approach in an MEC scenario to demonstrate high resource utilization and also keeping the request discard rate below 20%.

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On the Fine-Grained Crowd Analysis via Passive WiFi Sensing

TechRxiv

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TechRxiv 2023年

作者： Hao, Lifei Huang, Baoqi Jia, Bing Mao, Guoqiang The Engineering Research Center of Ecological Big Data Ministry of Education The Inner Mongolia A.R. Key Laboratory of Wireless Networking and Mobile Computing The College of Computer Science Inner Mongolia University Hohhot010021 China The Research Institute of Smart Transportation Xidian University Xi’an710071 China

Regarding the passive WiFi sensing based crowd analysis, this paper first theoretically investigates its limitations, and then proposes a deep learning based scheme targeted for returning fine-grained crowd states in large surveillance areas. To this end, three key challenges are coped with: to relieve the influences of the randomness and sparsity induced by passive WiFi sensing, an attention-based deep convolutional autoencoder model is designed to recover accurate crowd density maps in a way similar to image reconstruction;to combat the anonymity caused by MAC randomization, following the identification of local high-density crowds (LHDCs) with the density clustering algorithm, i.e. DM-DBSCAN, a bidirectional convolutional LSTM based model is employed to infer LHDC speeds;to overcome the absence of passive WiFi sensing datasets for model training, three semi-synthetic datasets are produced by emulating passive WiFi sensing with practical pedestrian tracking datasets. Extensive experiments confirm that, the proposed scheme significantly outperforms existing WiFi-based methods in terms of crowd density estimation and provides superior crowd speed estimation. More importantly, the scheme can also produce consistent crowd states on a real-world dataset, revealing that it has the ability to support accurate, visualized and real-time crowd monitoring in large surveillance areas. © 2023, CC BY-NC-SA.

关键词： Convolution

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Research on Data Collection Mechanism of wireless Sensor Network Based on UAV

Research on Data Collection Mechanism of Wireless Sensor Net...

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作者： Wen Xie Xiangyu Bai Inner Mongolia Key Laboratory of Wireless Networking and Mobile Computing Collece of Computer ScienceInner Mongolia University

In recent years, wireless Sensor networks（WSNs） have developed rapidly and have been widely used in various fields such as commerce, agriculture, military affairs and the environment. However,with the development of technology and the increasing demand of application scenarios, the limitations of WSNs are becoming more and more obvious. On the other hand, through continuous improvement, Unmanned Aerial Vehicle（UAV） technology has become more and more powerful, which can provide reliable, cost-effective services for people. The connectivity and energy efficiency of WSN can be significantly improved by taking advantage of UAV’s high altitude hovering capability, communication capability and flexible mobility. Many researchers believe that UAV assisted communication in WSN is a promising solution. In this paper, we first discuss the limitations of WSN in certain scenarios and the advantages of UAV-assisted WSN. Secondly, the development and research status of UAV-assisted wireless sensor network communication are introduced. In this process, this paper introduces the research status of three data collection methods: data storage and forwarding UAV, mobile relay UAV and aerial base station UAV, and discusses the research progress in the field of wireless communication of UAV. Finally, this paper compares and analyzes the above three types of UAV-assisted sensor network data collection methods, and prospects the future research of UAV-assisted WSN.

关键词： wireless sensor networks UAV Data collection aerial wireless relay mobile base station

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Trajectory Privacy Protection Method based on Shadow vehicles

Trajectory Privacy Protection Method based on Shadow vehicle...

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IEEE International Conference on Big Data and Cloud computing (BdCloud)

作者： Yaqiong Ma Xiangyu Bai Zhaoran Wang College of Computer Science Inner Mongolia University Inner Mongolia A.R. Key Laboratory of Wireless Networking and Mobile Computing Hohhot China

Location Based Services (LBS) are widely used in VANETs to provide a variety of services for vehicles. The trajectory privacy protection has attracted wide attention. However, there are some shortcomings in the schemes proposed at home and abroad. Therefore, this paper proposes a protection scheme based on shadow vehicles. First, the Genetic Algorithm is used to predict the trajectory, and suitable shadow vehicles are selected based on the deviation of the predicted trajectory. Then, a number of fake queries are inserted into the queries of real vehicles and shadow vehicles, finally a query matrix is formed and sent it to the LBS server for query. Fake queries make vehicle’s paths intersect, which can prevent the reverse mapping from vehicle’s identity to query content, so that the attacker can’t distinguish the complete trajectory of the target vehicle and the scheme can prevent continuous query attacks. Experiments have proved that the scheme improves the prediction similarity, the selected shadow vehicles are similar to the predicted trajectory of the real vehicle and the privacy protection of the trajectory is enhanced.

关键词： Location awareness Privacy Trajectory Servers Genetic algorithms

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A Channel Adaptive WiFi Indoor Localization Method based on Deep Learning

A Channel Adaptive WiFi Indoor Localization Method based on ...

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IEEE Conference on wireless Communications and networking

作者： Lifei Hao Baoqi Huang Hao Hong Bing Jia Wuyungerile Li Inner Mongolia A.R. Key Laboratory of Wireless Networking and Mobile Computing Hohhot China College of Computer Science Inner Mongolia University Hohhot China

ISBN: (纸本)9781728195056;9781728195063

With the increasing demand on Indoor Location-Based Services (ILBS), various positioning technologies had emerged in the past decades, and WiFi-based approach is one of the most promising ones. However, the existing WiFi localization methods fail to take into account the disparate influence of packets transmitted in different channels so as to inhibit the further improvement of localization accuracy. Therefore, we present CADNN: a Channel Adaptive WiFi localization method based on Deep Neural Network (DNN). Specifically, a comprehensive analysis on signal attenuations in different channels along with error analysis based on Cramer-Rao Lower Bound (CRLB) is conducted in theory. Then, the channel set splitting scheme for practical localization to leverage multi-channel features is proposed. Finally, we design a localization framework using multi-objective regression DNN to adapt Received Signal Strength (RSS) measurements from different channel sets. The results from real-world experiments confirm the effectiveness of channel adaptive and show that CADNN can improve localization accuracy by at least 25.3% and 19.5% respectively on the two datasets and it can serve thousands users within one second.

关键词： Location awareness Deep learning Adaptive systems Error analysis Conferences Neural networks Measurement uncertainty

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key nodes recognition in opportunistic network 6th

Key nodes recognition in opportunistic network

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6th International Symposium on Security and Privacy in Social Networks and Big Data, SocialSec 2020

作者： Wang, Zhifei Xu, Gang Wei, Fengqi Qi, Zhihan He, Liqiang College of Computer Science Inner Mongolia University Hohhot China Inner Mongolia A.R. Key Laboratory of Wireless Networking and Mobile Computing Hohhot China Geomechanica Inc. Toronto Canada

ISBN: (纸本)9789811590306

There are always communication fragmented regions in opportunistic networks, and Ferry nodes which can periodicity commute between different fragmented regions always be placed in opportunistic networks. At present, the research on Ferry nodes in opportunistic networks mainly focus on the cache management, energy balance and routing algorithm optimization, meanwhile, researches on identifying Ferry nodes in a strange network are less. On the basis of the importance of structure holes and k-cores, this paper puts forward the index to evaluate the dynamic importance of nodes in opportunistic network, and proposes an importance evaluation algorithm of nodes in opportunistic networks based on it, which is used to identify the Ferry nodes clusters in strange networks. Conclusions can draw through experiments that the proposed model has good applicability and can identify Ferry nodes in networks accurately. © Springer Nature Singapore Pte Ltd 2020.

关键词： Clustering algorithms

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Counting mobile Devices With Physical Layer Measurements in the 2.4GHz ISM Band

Counting Mobile Devices With Physical Layer Measurements in ...

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted computing, UIC-ATC

作者： Zhaoyan Zhang Baoqi Huang Chaowei Zhang Bing Jia Wuyungerile Li Gang Xu Engineering Research Center of Ecological Big Data Ministry of Education Inner Mongolia Key Laboratory of Wireless Networking and Mobile Computing Hohhot China College of Computer Science Inner Mongolia University Hohhot China Inner Mongolia Power Marketing Service and Operation Management Center

In general, the more mobile devices are operating in space, the more wireless communications are produced, leading to significant changes in the wireless spectrum, which can be utilized to infer the number of mobile devices conversely. Inspired by this idea, we pioneered present a novel mobile device counting method of measuring the wireless signals of the 2. 4GHz ISM band in which most WiFi-and Bluetooth-enabled mobile devices operate. Precisely, the in-phase (I) and quadrature (Q) components from the wireless signals are measured through a software-defined radio (SDR) platform and are then converted into spectrograms. On this ground, we propose a dual attention network based on EfficientNet-B4 (EANet) to estimate the number of mobile devices with the aforementioned spectrograms as inputs. In addition, a cross-domain estimation method is proposed to enhance the generalizability of our model. Experiments are conducted in real environments to validate our method. It is shown that the proposed regression model EANet outperforms the models based on popular convolutional neural networks (CNNs), and the proposed cross-domain method can effectively reduce the training time without sacrificing the estimation accuracy. This study preliminarily verifies the idea’s feasibility and the validity of the proposed methods, paving the way for future research.

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Toward Wisdom-Evolutionary and Primitive-Concise 6G:A New Paradigm of Semantic Communication Networks

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Engineering 2022年第1期8卷 60-73页

作者： Ping Zhang Wenjun Xu Hui Gao Kai Niu Xiaodong Xu Xiaoqi Qin Caixia Yuan Zhijin Qin Haitao Zhao Jibo Wei Fangwei Zhang State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China Peng Cheng Laboratory Shenzhen 518066China Key Laboratory of Universal Wireless Communications Ministry of EducationBeijing University of Posts and TelecommunicationsBeijing 100876China Key Laboratory of Trustworthy Distributed Computing and Service Ministry of EducationBeijing University of Posts and TelecommunicationsBeijing 100876China School of Artificial Intelligence Beijing University of Posts and TelecommunicationsBeijing 100876China The School of Electronic Engineering and Computer Science Queen Mary University of LondonLondon E14NSUK College of Electronic Science and Technology National University of Defense TechnologyChangsha 410073China School of Humanities Beijing University of Posts and TelecommunicationsBeijing 100876China

The sixth generation(6G)mobile networks will reshape the world by offering instant,efficient,and intelligent hyper-connectivity,as envisioned by the previously proposed Ubiquitous-X 6G *** hyper-massive and global connectivity will introduce tremendous challenges into the operation and management of 6G networks,calling for revolutionary theories and technological *** this end,we propose a new route to boost network capabilities toward a wisdom-evolutionary and primitive-concise network(WePCN)vision for the Ubiquitous-X 6G *** particular,we aim to concretize the evolution path toward the WePCN by first conceiving a new semantic representation framework,namely semantic base,and then establishing an intelligent and efficient semantic communication(IE-SC)network *** the IE-SC architecture,a semantic intelligence plane is employed to interconnect the semantic-empowered physical-bearing layer,network protocol layer,and application-intent layer via semantic information *** proposed architecture integrates artificial intelligence and network technologies to enable intelligent interactions among various communication objects in *** features a lower bandwidth requirement,less redundancy,and more accurate intent *** also present a brief review of recent advances in semantic communications and highlight potential use cases,complemented by a range of open challenges for 6G.

关键词： 6G Semantic information Semantic communication Intelligent communication

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Research on VANET Network Coding Strategy in Expressway Scene

Research on VANET Network Coding Strategy in Expressway Scen...

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International Conference on Information and Communication Technologies for Disaster Management (ICT-DM)

作者： Hua Zhang Xiangyu Bai Lei Yao Inner Mongolia A.R. Key Laboratory of Wireless Networking and Mobile Computing School of Computer Science Inner Mongolia University Hohhot Inner Mongolia Autonomous Region China

ISBN: (纸本)9781665432863

VANET is a real-time, intelligent transportation network featuring motion patterns limited by roads, diverse transmission data, and frequent topological changes. In the highway scene, the network coding and the roadside unit are introduced to assist the data transmission in order to solve such problems as single data transmission path and short communication link duration. When the vehicle node transmits data, it will first determine the type of vehicle node at this time, and select the best transmission path as the main path of the encoded data packet according to the relative position information of the vehicle nodes, the difference of the requested content storage nodes, and the vehicle density. The path acts as a secondary path for the transmission of encoded packets. Finally, the routing strategy proposed in this paper is implemented by the opportunistic network simulator ONE simulation. According to the experimental results, the routing strategy proposed in this paper can effectively improve the message delivery rate, reduce the average network delay and network overhead.

关键词： Roads Vehicular ad hoc networks Transportation Disaster management Network coding Routing Real-time systems

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