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4th International Conference on Information Science and Systems, ICISS 2021

作者： Cai, Ziyin Yang, Meng Cui, Hongyan Li, Xiaoqiu Xu, Meng State Key Lab of Networking and Switching Tech Beijing University of Post and Telecommunication China Big Data Application Department China Mobile Information Technology Co. Ltd China Research and Development Centre China National Offshore Oil Corp Safety Technology Service Co. Ltd China

ISBN: (纸本)9781450389136

The blockchain is a decentralized network, which can prevent information to be tampered and improves the security and transparency of data. Traditional centralized database to store logistics data is vulnerable to attacks and limits sharing of information. Information isolation and unreliable data make it hard to trace the process of logistics delivery. In this paper, we propose a blockchain based system to improve the performance of logistics tracing service. We design the overall structure of the blockchain system and build a prototype using Hyperledger Fabric. Smart contract is implemented to store the logistic records into the blockchain ledgers and create tracing lists for logistic orders. Performance evaluation shows that the system achieves the logistics tracing ability with good performance. This paper assumes that the IoT devices used in the logistics process are reliable and will not be attacked. In the further work, a smart contract-based access control model can be developed to overcome the vulnerability caused by IoT devices. © 2021 ACM.

关键词： Blockchain

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3GPP-Like GBSM THz Channel Characterization, Modeling, and Simulation Based on Experimental Observations

arXiv

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arXiv 2023年

作者： Chang, Zhaowei Zhang, Jianhua Tang, Pan Tian, Lei Jiang, Hao Liu, Ximan Liu, Guangyi State Key Lab of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China School of Artificial Intelligence School of Future Technology Nanjing University of Information Science and Technology Nanjing210044 China National Mobile Communications Research Laboratory Southeast University Nanjing210096 China China Mobile Research Institute Beijing100053 China

Terahertz (THz) communication is envisioned as one of the possible technologies for the sixth-generation (6G) communication system due to its rich spectrum. To evaluate the performance of THz communication, it is essential to propose THz channel models within the common framework of the geometry-based stochastic model (GBSM) in the 3rd Generation Partnership Project (3GPP). This paper focuses on THz channel modeling and simulation by a 3GPP-like GBSM, based on channel measurements. We first present channel measurements at 100 GHz in an indoor office scenario and 132 GHz in an urban microcellular scenario. Subsequently, channel characteristics such as path loss, delay spread, angle spread, K-factor, cluster characteristic, cross-correlations, and correlation distances are obtained and analyzed based on channel measurement. Additionally, the channel characteristics are modeled by the statistical distribution of 3GPP channel models, which can be used to reconstruct the channel impulse response (CIR). Furthermore, these obtained distributions are studied referring to the default models in the 3GPP, revealing the channel sparsity in the THz channel. For instance, in the case of line-of-sight links in the indoor office, the mean of the measured cluster number is 4 while the default value is 15. Finally, we propose the THz channel model and its simulation framework to reconstruct CIRs based on the obtained models, which aim at characterizing the sparser THz channels. The obvious channel sparsity is characterized in both scenarios, as the Gini factors obtained by the proposed model only have the maximum deviation of 0.04 for those of the measurement. Overall, these findings are helpful in understanding and modeling the THz channel, facilitating the application of THz communication techniques for 6G. Copyright © 2023, The Authors. All rights reserved.

关键词： Stochastic systems

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A Study on Multidimensional Medical Data Processing Based on Random Forest 5

A Study on Multidimensional Medical Data Processing Based on...

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5th International Conference on Universal Village, UV 2020

作者： Zhang, Lifeng Cui, Hongyan Welsch, Roy E. Beijing University of Posts and Telecommunications Beijing Lab. of Advanced Information Networks State Key Lab. of Networking and Switching Technology Beijing China Massachusetts Institute of Technology Cambridge United States

ISBN: (纸本)9781728195230

Medical detection is one of the important methods to prevent, diagnose and treat diseases. Under normal conditions, there are many indicators as the basis for diagnosis in medical detection usually. However, in some situations, many detection indicators, useful or important, account for a small proportion, which causes a certain cost. On the other hand, so many indicators also give inexperienced researchers difficulty in making precise decisions on the diagnosis of disease status based on more important indicators. We propose a method of multidimensional data processing based on random forest in this paper, aiming to reduce the difficulties in medical multidimensional data. We proposed a method based on Random Forest according to impact score, to classify multi-dimensional attributes as strong impact and weak impact for disease. The experimental dataset is diabetic retinopathy from the UIC. In the experiment, we designed a method based on random forest according to impact score, to classify multi-dimensional attributes as strong impact and weak impact for disease. The experimental result shows that the higher-score group has better performance in diagnosing diabetic retinopathy. © 2020 IEEE.

关键词： Random forests

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Automated Performance Benchmarking Platform of IaaS Cloud

Automated Performance Benchmarking Platform of IaaS Cloud

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Xu Liu Dongxu Fang Peng Xu China Academy of Industrial Internet Beijing China State Key Lab of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781665416597

With the rapid development of cloud computing, IaaS (Infrastructure as a Service) becomes more and more popular. IaaS customers may not clearly know the actual performance of each cloud platform. Moreover, there are no unified standards in performance evaluation of IaaS VMs (virtual machine). The underlying virtualization technology of IaaS cloud is transparent to customers. In this paper, we will design an automated performance benchmarking platform which can automatically install, configure and execute each benchmarking tool with a configuration center. This platform can easily visualize multidimensional benchmarking parameters data of each IaaS cloud platform. We also rented four IaaS VMs from AliCloud-Beijing, AliCloud-Qingdao, UCloud and Huawei to validate our benchmarking system. Performance comparisons of multiple parameters between multiple platforms were shown in this paper. However, in practice, customers' applications running on VMs are often complex. Performance of complex applications may not depend on single benchmarking parameter (e.g. CPU, memory, disk I/O etc.). We ran a TPC-C test for example to get overall performance in MySQL application scenario. The effects of different benchmarking parameters differ in this specific scenario.

关键词： Performance evaluation Cloud computing Privacy Fluctuations Data visualization Benchmark testing Virtual machining

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BANANA: When behavior ANAlysis meets social network alignment 29

BANANA: When behavior ANAlysis meets social network alignmen...

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29th International Joint Conference on Artificial Intelligence, IJCAI 2020

作者： Ren, Fuxin Zhang, Zhongbao Zhang, Jiawei Su, Sen Sun, Li Zhu, Guozhen Guo, Congying State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China IFM Lab Department of Computer Science Florida State University FL United States

ISBN: (纸本)9780999241165

Recently, aligning users among different social networks has received significant attention. However, most of the existing studies do not consider users' behavior information during the aligning procedure and thus still suffer from the poor learning performance. In fact, we observe that social network alignment and behavior analysis can benefit from each other. Motivated by such an observation, we propose to jointly study the social network alignment problem and user behavior analysis problem. We design a novel end-to-end framework named BANANA. In this framework, to leverage behavior analysis for social network alignment at the distribution level, we design an earth mover's distance based alignment component to fuse users' behavior information for more comprehensive user representations. To further leverage social network alignment for behavior analysis, in turn, we design a temporal graph neural network component to fuse behavior information in different social networks based on the alignment result. Two models above can work together in an end-to-end manner. Through extensive experiments on real-world datasets, we demonstrate that our proposed approach outperforms the state-of-the-art methods in the social network alignment task and the user behavior analysis task, respectively. © 2020 Inst. Sci. inf., Univ. Defence in Belgrade. All rights reserved.

关键词： Alignment

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Design and Implementation of Intelligent Operation and Maintenance System for Big Data Platform

Design and Implementation of Intelligent Operation and Maint...

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Xu Liu Ruoyu Li Penghao Yue China Academy of Industrial Internet Beijing China State Key Lab of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781665416597

In recent years, with the development of big data technologies and applications, more and more enterprises realize that big data will play an important role in enterprises, which leads to a significant increase of big data platforms adopted by enterprises. Intelligent operation and maintenance could complete system state evaluation, abnormal diagnosis, alarm and prediction by means of data analysis, so as to reduce the complexity and workload of system operation and maintenance. In order to simplify the operation and maintenance of big data platform, intelligent operation and maintenance of big data platform has become a trend. In this context, the intelligent operation and maintenance system for big data platform is designed and implemented. The system realizes the collection, aggregation and storage, analysis with query and visualization of the runtime data of the big data platform. By providing a series of intelligent operation and maintenance functions, the complexity and workload of operation and maintenance personnel are reduced. In this thesis, the unified scoring model of big data platform is proposed; the HDFS capacity prediction method is proposed to manage the storage capacity of big data platform more actively; the task scheduling method based on platform free time analysis is proposed to optimize the platform efficiency.

关键词： Analytical models Data analysis Systems operation Time series analysis Big Data Maintenance engineering Data models

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Modeling of Path Loss Characteristics in a Waveguide-Like Structure Scenario at 28 GHz

Modeling of Path Loss Characteristics in a Waveguide-Like St...

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European Conference on Antennas and Propagation, EuCAP

作者： Qidu Song Pan Tang Tao Jiang Lei Tian Jianhua Zhang Jianwu Dou State Key Lab of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China ZTE Corporation Shenzhen China State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen China

Radio wave propagation in a waveguide-like structure scenario performs a specific path loss characteristic which is termed as waveguide effect. In this paper, we analyze the path loss characteristics in a waveguide-like structure scenario based on channel measurements at 28 GHz. First, three different modeling methods, including the waveguide approach, ray-tracing approach, and empirical approach, are compared and validated with the measurement results. This study suggests that the empirical dual-slope channel model can give a more accurate prediction of path loss with minimum root mean square error (RMSE). Secondly, the influence of the geometry position of antennas on path loss is investigated by using the dual-slope path loss model. Comparative analysis results reveal that a stronger waveguide effect exists when placing the antenna close to the wall and when having antenna height difference, horizontal measurements at different line-of-sight distances confirm the analysis that waveguide effect exists after the breakpoint.

关键词： Antenna measurements Geometry Antenna theory Propagation Millimeter wave measurements Waveguide theory Ray tracing

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Research and Experimental Validation for 3GPP ISAC Channel Modeling Standardization

arXiv

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arXiv 2025年

作者： Zhang, Yuxiang Zhang, Jianhua Zhang, Jiwei Pei, Yuanpeng Liu, Yameng Tian, Lei Jiang, Tao Liu, Guangyi China Mobile Research Institute Beijing Beijing100053 China State Key Lab of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

Integrated Sensing and Communication (ISAC) is considered a key technology in 6G networks. An accurate sensing channel model is crucial for the design and sensing performance evaluation of ISAC systems. The widely used Geometry-Based Stochastic Model (GBSM), typically applied in standardized channel modeling, mainly focuses on the statistical fading characteristics of the channel. However, it fails to capture the characteristics of targets in ISAC systems, such as their positions and velocities, as well as the impact of the targets on the background. To address this issue, this paper proposes an extended GBSM (E-GBSM) sensing channel model that incorporates newly discovered channel characteristics into a unified modeling framework. In this framework, the sensing channel is divided into target and background channels. For the target channel, the model introduces a concatenated modeling approach, while for the background channel, a parameter called the power control factor is introduced to assess impact of the target on the background channel, making the modeling framework applicable to both mono-static and bi-static sensing modes. To validate the proposed model’s effectiveness, measurements of target and background channels are conducted in both indoor and outdoor scenarios, covering various sensing targets such as metal plates, reconfigurable intelligent surfaces, human bodies, UAVs, and vehicles. The experimental results provide important theoretical support and empirical data for the standardization of ISAC channel modeling. Copyright © 2025, The Authors. All rights reserved.

关键词： Fading channels

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Distributed Systems Anomaly Detection Based on Log

Distributed Systems Anomaly Detection Based on Log

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

作者： Fenggang Lai Pan Zhang Ruiying Cheng Peng Xu State Grid Information and Telecommunication Co. Ltd. Beijing China State Key Lab of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781665432863

Benefiting from the rapid development of information technology, distributed systems have been widely used. A distributed system consists of a large number of parts (nodes/components), so its maintenance usually requires plenty of manual work. To reduce the complexity and workload of the operation and maintenance of the complex system, more and more log anomaly detection methods are used for large-scale distributed systems. However, these methods do not consider the time and space characteristics of logs. To bridge this gap, we brought forward an anomaly detection method based on logs generated by distributed systems. We design a template parsing algorithm to parse logs through the Transformer encoder and two clusters of different granularities. We use an anomaly detection algorithm to capture anomalies in time and space through the combination of CNN, LSTM, and attention mechanism. In addition, we optimize the detection window by combining the session window with the sliding window, and we optimize the computational complexity by changing the connection between LSTM and CNN.

关键词： Clustering algorithms Manuals Disaster management Maintenance engineering Transformers Feature extraction Information and communication technology

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Fully-Passive versus Semi-Passive IRS-Enabled Sensing: SNR and CRB Comparison

arXiv

引用

arXiv 2023年

作者： Song, Xianxin Li, Xinmin Qin, Xiaoqi Xu, Jie Han, Tony Xiao Ng, Derrick Wing Kwan Shenzhen518172 China The School of Information Engineering Southwest University of Science and Technology Mianyang621000 China Shenzhen518172 China The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China The 2012 lab Huawei Shenzhen518129 China The School of Electrical Engineering and Telecommunications University of New South Wales SydneyNSW2052 Australia

This paper investigates the sensing performance of two intelligent reflecting surface (IRS)-enabled non-line-of-sight (NLoS) sensing systems with fully-passive and semi-passive IRSs, respectively. In particular, we consider a fundamental setup with one base station (BS), one uniform linear array (ULA) IRS, and one point target in the NLoS region of the BS. Accordingly, we analyze the sensing signal-to-noise ratio (SNR) performance for a target detection scenario and the estimation Cramér-Rao bound (CRB) performance for a target’s direction-of-arrival (DoA) estimation scenario, in cases where the transmit beamforming at the BS and the reflective beamforming at the IRS are jointly optimized. First, for the target detection scenario, we characterize the maximum sensing SNR when the BS-IRS channels are line-of-sight (LoS) and Rayleigh fading, respectively. It is revealed that when the number of reflecting elements N equipped at the IRS becomes sufficiently large, the maximum sensing SNR increases proportionally to N2 for the semi-passive-IRS sensing system, but proportionally to N4 for the fully-passive-IRS counterpart. Then, for the target’s DoA estimation scenario, we analyze the minimum CRB performance when the BS-IRS channel follows Rayleigh fading. Specifically, when N grows, the minimum CRB decreases inversely proportionally to N4 and N6 for the semi-passive and fully-passive-IRS sensing systems, respectively. Finally, numerical results are presented to corroborate our analysis across various transmit and reflective beamforming design schemes under general channel setups. It is shown that the fully-passive-IRS sensing system outperforms the semi-passive counterpart when N exceeds a certain threshold. This advantage is attributed to the additional reflective beamforming gain in the IRS-BS path, which efficiently compensates for the path loss for a large N. Copyright © 2023, The Authors. All rights reserved.

关键词： Signal to noise ratio

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