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Intelligent Internet of Things with Reliable Communication and Collaboration Technologies

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China Communications 2024年第8期21卷 I0002-I0006页

作者： Zhao Junhui wu celimuge Xu Wenjun Qi Chenhao Bu Shengrong Zhang Shuowen Zhang Qingmiao the School of Electronics and Information Engineering Beijing Jiaotong University the School of Information Engineering in East China Jiaotong University Meta-Networking Research Center the University of Electro-Communications the School of Artificial Intelligence BUPT State Key Laboratory of Networking and Switching Technology the Peng Cheng Laboratory the faculty of the School of Information Science and Engineering Southeast University Brock University the Hong Kong Polytechnic University East China Jiaotong University

The Internet of Things(IoT)connects objects to Internet through sensor devices,radio frequency identification devices and other information collection and processing devices to realize information *** is widely used in many fields,including intelligent transportation,intelligent healthcare,intelligent home and *** these fields,IoT devices connected via high-speed internet for efficient and reliable communications and faster response times.

关键词： interaction Internet IoT

GUEST EDITORIAL Intelligent Internet of Things with Reliable Communication and Collaboration Technologies

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China Communications 2024年第8期 4-8页

The Internet of Things(IoT) connects objects to Internet through sensor devices, radio frequency identification devices and other information collection and processing devices to realize information interaction. IoT is widely used in many fields, including intelligent transportation, intelligent healthcare, intelligent home and industry.

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Frequent Itemset Mining of User’s Multi-Attribute under Local Differential Privacy

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Computers, Materials & Continua 2020年第10期65卷 369-385页

作者： Haijiang Liu Lianwei Cui Xuebin Ma celimuge wu College of Computer Science Inner Mongolia UniversityHohhot010020China Inner Mongolia Big Data Development Authority Hohhot010020China Graduate School of Informatics and Engineering the University of Electro-CommunicationTokyo182-8585Japan

Frequent itemset mining is an essential problem in data mining and plays a key role in many data mining ***,users’personal privacy will be leaked in the mining *** recent years,application of local differential privacy protection models to mine frequent itemsets is a relatively reliable and secure protection *** differential privacy means that users first perturb the original data and then send these data to the aggregator,preventing the aggregator from revealing the user’s private *** propose a novel framework that implements frequent itemset mining under local differential privacy and is applicable to user’s *** main technique has bitmap encoding for converting the user’s original data into a binary *** also includes how to choose the best perturbation algorithm for varying user attributes,and uses the frequent pattern tree(FP-tree)algorithm to mine frequent ***,we incorporate the threshold random response(TRR)algorithm in the framework and compare it with the existing algorithms,and demonstrate that the TRR algorithm has higher accuracy for mining frequent itemsets.

关键词： Local differential privacy frequent itemset mining user’s multi-attribute

A Recommendation Approach Based on Bayesian Networks for Clone Refactor

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Computers, Materials & Continua 2020年第9期64卷 1999-2012页

作者： Ye Zhai celimuge wu Dongsheng Liu Rongrong She Inner Mongolia Normal University Hohhot010022China Graduate School of Informatics and Engineering The University of Electro-CommunicationsTokyo182-8585Japan

Reusing code fragments by copying and pasting them with or without minor adaptation is a common activity in software *** a result,software systems often contain sections of code that are very similar,called code *** clones are beneficial in reducing software development costs and development ***,recent studies have indicated some negative impacts as a *** order to effectively manage and utilize the clones,we design an approach for recommending refactoring clones based on a Bayesian ***,clone codes are detected from the source ***,the clones that need to be refactored are identified,and the static and evolutions features are extracted to build the feature ***,the Bayesian network classifier is used for training and evaluating the classification *** on more than 640 refactor examples of five open source software developed in C,we observe a considerable *** results show that the accuracy of the approach is larger than 90%.We believe our approach will provide a more accurate and reasonable code refactoring and maintenance advice for software developers.

关键词： Clone code clone refactor feature extraction Bayesian network

Time-Critical Tasks Implementation in MEC Based Multi-Robot Cooperation Systems

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China Communications 2022年第4期19卷 199-215页

作者： Rui Yin Yineng Shen Huawei Zhu Xianfu Chen celimuge wu School of Information and Electrical Engineering Zhejiang University City CollegeHangzhou 310015China School of Information and Electrical Engineering Zhejiang UniversityHangzhou 310027China The VTT Technical Research Centre of Finland Oulu90570Finland Graduate School of Informatics and Engineering the University of Electro-CommunicationsTokyo182-8585Japan

Mobile edge computing(MEC) deployment in a multi-robot cooperation(MRC) system is an effective way to accomplish the tasks in terms of energy consumption and implementation latency. However, the computation and communication resources need to be considered jointly to fully exploit the advantages brought by the MEC technology. In this paper, the scenario where multi robots cooperate to accomplish the time-critical tasks is studied, where an intelligent master robot(MR) acts as an edge server to provide services to multiple slave robots(SRs) and the SRs are responsible for the environment sensing and data collection. To save energy and prolong the function time of the system, two schemes are proposed to optimize the computation and communication resources, respectively. In the first scheme, the energy consumption of SRs is minimized and balanced while guaranteeing that the tasks are accomplished under a time constraint. In the second scheme, not only the energy consumption, but also the remaining energies of the SRs are considered to enhance the robustness of the system. Through the analysis and numerical simulations, we demonstrate that even though the first policy may guarantee the minimization on the total SRs’ energy consumption, the function time of MRC system by the second scheme is longer than that by the first one.

关键词： cooperative robots mobile edge computing energy consumption resource management

COLLABORATIVE INTELLIGENCE FOR VEHICULAR INTERNET OF THINGS

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China Communications 2021年第7期18卷 I0003-I0006页

作者： celimuge wu Kok-Lim Alvin Yau Carlos Tavares Calafate Lei Zhong University of Electro-Communications since IEEE TCGCC Special Interest Group on Green Internet IEEE TCBD Special Interest Group on Big Data with Computational Intelligence Department of Computing and Information Systems Sunway University Department of Computer Engineering at the Technical University of Valencia(UPV)in Spain Connected Advanced Development Division at Toyota Motor Corporation

Future vehicular Internet-of-Things(IoT)systems feature a large number of devices and multi-access environments where different types of communication,computing,and storage resources must be efficiently *** the same time,novel services such as cooperative autonomous driving and intelligent transportation systems(ITS),that demand unprecedented high accuracy,ultra-low latency,and large bandwidth,are emerging.

关键词： INTERNET services utilized

Edge Computing-Based Joint Client Selection and Networking Scheme for Federated Learning in Vehicular IoT

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China Communications 2021年第6期18卷 39-52页

作者： wugedele Bao celimuge wu Siri Guleng Jiefang Zhang Kok-Lim Alvin Yau Yusheng Ji School of computer science and information engineering Hohhot Minzu CollegeHohhot 010051China Graduate School of Informatics and Engineering The University of Electro-Communications1-5-1ChofugaokaChofu-shiTokyo182-8585 Japan Institute of Intelligent Media Technology Communication University of ZhejiangZhejiang 310018China School of Science and Technology Sunway University5Jalan UniversitiBandar Sunway47500 Petaling JayaSelangorMalaysia Information Systems Architecture Research Division National Institute of Informatics2-1-2HitotsubashiChiyoda-kuTokyo 101-8430 Japan

In order to support advanced vehicular Internet-of-Things(IoT)applications,information exchanges among different vehicles are required to find efficient solutions for catering to different application requirements in complex and dynamic vehicular *** learning(FL),which is a type of distributed learning technology,has been attracting great interest in recent years as it performs knowledge exchange among different network entities without a violation of user ***,client selection and networking scheme for enabling FL in dynamic vehicular environments,which determines the communication delay between FL clients and the central server that aggregates the models received from the clients,is still *** this paper,we propose an edge computing-based joint client selection and networking scheme for vehicular *** proposed scheme assigns some vehicles as edge vehicles by employing a distributed approach,and uses the edge vehicles as FL clients to conduct the training of local models,which learns optimal behaviors based on the interaction with *** clients also work as forwarder nodes in information sharing among network *** client selection takes into account the vehicle velocity,vehicle distribution,and the wireless link connectivity between vehicles using a fuzzy logic algorithm,resulting in an efficient learning and networking *** use computer simulations to evaluate the proposed scheme in terms of the communication overhead and the information covered in learning.

关键词： vehicular IoT federated learning client selection networking scheme

基于深度强化学习的海洋移动边缘计算卸载方法

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通信学报 2022年第10期43卷 133-145页

作者：苏新孟蕾蕾周一青 celimuge wu 河海大学物联网工程学院江苏常州231022 中国科学院计算技术研究所处理器芯片全国重点实验室北京100190 中国科学院大学计算机科学与技术学院北京100190 日本电气通信大学信息理工学院东京182-8585

海洋信息系统网络节点之间的强异构特性为海洋移动边缘计算任务卸载优化带来了复杂高维度的限制条件,同时复杂多样化的海事应用会导致海洋网络局部区域出现计算任务的超负荷处理。为实现海洋网络节点计算任务的最佳卸载与资源优化,满足... 详细信息

海洋信息系统网络节点之间的强异构特性为海洋移动边缘计算任务卸载优化带来了复杂高维度的限制条件,同时复杂多样化的海事应用会导致海洋网络局部区域出现计算任务的超负荷处理。为实现海洋网络节点计算任务的最佳卸载与资源优化,满足网络低时延、高可靠的应用服务需求,提出基于多尺度异构特征属性的海洋网络节点分层归类方法和基于深度强化学习的海洋移动边缘计算卸载方法。仿真结果表明,所提方法较传统方法能够在海洋信息系统下有效地降低网络节点的计算任务卸载时延,并且能够在大规模任务流下保持海洋网络的稳健性。

关键词：海洋信息系统边缘计算计算任务卸载功率与计算资源分配深度强化学习

A Cooperative Forwarding Scheme for VANET Routing Protocols

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ZTE Communications 2016年第3期14卷 13-21页

作者： wu celimuge JI Yusheng YOSHINAGA Tsutomu The University of Electro-Communications Chofu-shi Tokyo 182-8585 Japan National Institute of Informatics Chiyoda-ku Tokyo 101-8430 Japan

Providing efficient packet delivery in vehicular ad hoc networks （VANETs） is particularly challenging due to the vehicle move- ment and lossy wireless channels. A data packet can be lost at a forwarding node even when a proper node is selected as the for- warding node. In this paper, we propose a loss-tolerant scheme for unicast routing protocols in VANETs. The proposed scheme employs multiple forwarding nodes to improve the packet reception ratio at the forwarding nodes. The scheme uses network coding to reduce the number of required transmissions, resulting in a significant improvement in end-to-end packet delivery ratio with low message overhead. The effectiveness of the proposed scheme is evaluated by using both theoretical analysis and computer sim-

关键词： vehicular ad hoe networks routing protocol network coding cooperative forwarding scheme