Updated on 2022/05/25

写真a

 
WEN, Zheng
 
Affiliation
Faculty of Science and Engineering, School of Fundamental Science and Engineering
Job title
Assistant Professor(without tenure)

Research Institute

  • 2020
    -
    2022

    国際情報通信研究センター   兼任研究員

Education

  • 2013.09
    -
    2019.02

    Waseda University  

  • 2005.09
    -
    2009.06

    Wuhan University  

Degree

  • Waseda University   Ph.D.

Professional Memberships

  •  
     
     

    IEEE

  •  
     
     

    IEICE

 

Research Areas

  • Information network

Research Interests

  • Data Science

  • IoT

  • Blockchain

  • Artificial Intelligence

  • Communication Network

  • Disaster Management

  • Content-oriented Networking

▼display all

Papers

  • Blockchain–a promising solution to internet of things: A comprehensive analysis, opportunities, challenges and future research issues

    Anup Kumar Paul, Xin Qu, Zheng Wen

    Peer-to-Peer Networking and Applications   14 ( 5 ) 2926 - 2951  2021.09

     View Summary

    Blockchain (BC) technology is a promising answer for providing security and ensuring protection in a distributed way. It has transformed the digital currency platform with the revolutionary crypto-currency known as Bitcoin. From a theoretical point of view, a BC is a distributed series of blocks linked with each other where every block is an immutable record of some form of data exchange occurring in a network. Recently, numerous literature reviews and research articles have been published on the combination of BC with the Internet of Things (IoT). However, they are restricted to shallow conversations of specialized possibilities, and not many of them have an exhaustive investigation of the difficulties in creating BC for IoT at implementation levels. Within this frame of reference, the BC is viewed as the important link for creating a genuinely secure, decentralized, and trustless platform designed to be used in IoT and, in this literature review, we mean to figure out an intelligent and thorough image of the present progressive research works toward this path. We begin with the security vulnerabilities presented by the different IoT layers. Then we focused on the central working principle of BC and how BC-based frameworks accomplish the feature of security, decentralization, and auditability. From that point, we focused on the security solutions to several vulnerabilities presented by the IoT with centralized architecture, accompanied by ongoing industrial advancement and academic research to comprehend these difficulties and successfully use BC to ensure a secure platform without any centralized management in IoT.

    DOI

  • Content-oriented Multicamera Trajectory Forecasting Surveillance Network System

    Xin Qi, Toshio Sato, Keping Yu, San Hlaing Myint, Yutaka Katsuyama, Kazuhiko Tamesue, Kiyohito Tokuda, Zheng Wen, Takuro Sato

    2021 Twelfth International Conference on Ubiquitous and Future Networks (ICUFN)   2021-August   17 - 22  2021.08

     View Summary

    To reduce safety violations in wide-area ranges, there is a need for highly functional multicamera surveillance systems. We introduce a multicamera trajectory forecasting surveillance network system based on a content-oriented suspicious object network system. This system uses multiple cameras in detection and recognition to track persons among different areas and is capable of retracking people. Each camera node has a processing unit and uses information-centric networking technology to build a content-oriented IoT network. We use field-recorded data to support the simulation, and the evaluation result indicates that our trajectory forecasting method is more efficient than conventional surveillance systems.

    DOI

  • Position Estimation of Pedestrians in Surveillance Video Using Face Detection and Simple Camera Calibration

    Toshio Sato, Xin Qi, Keping Yu, Zheng Wen, Yutaka Katsuyama, Takuro Sato

    2021 17th International Conference on Machine Vision and Applications (MVA)    2021.07

     View Summary

    Pedestrian position estimation in videos is an important technique for enhancing surveillance system applications. Although many studies estimate pedestrian positions by using human body detection, its usage is limited when the entire body expands outside of the field of view. Camera calibration is also important for realizing accurate position estimation. Most surveillance cameras are not adjusted, and it is necessary to establish a method for easy camera calibration after installation. In this paper, we propose an estimation method for pedestrian positions using face detection and anthropometric properties such as statistical face lengths. We also investigate a simple method for camera calibration that is suitable for actual uses. We evaluate the position estimation accuracy by using indoor surveillance videos.

    DOI

  • Deep-learning-empowered 3D reconstruction for dehazed images in IoT-Enhanced smart cities

    Jing Zhang, Xin Qi, San Hlaing Myint, Zheng Wen

    Computers, Materials and Continua   68 ( 2 ) 2807 - 2824  2021.04

     View Summary

    With increasingly more smart cameras deployed in infrastructure and commercial buildings, 3D reconstruction can quickly obtain cities' information and improve the efficiency of government services. Images collected in outdoor hazy environments are prone to color distortion and low contrast; thus, the desired visual effect cannot be achieved and the difficulty of target detection is increased. Artificial intelligence (AI) solutions provide great help for dehazy images, which can automatically identify patterns or monitor the environment. Therefore, we propose a 3D reconstruction method of dehazed images for smart cities based on deep learning. First, we propose a fine transmission image deep convolutional regression network (FT-DCRN) dehazing algorithm that uses fine transmission image and atmospheric light value to compute dehazed image. The DCRN is used to obtain the coarse transmission image, which can not only expand the receptive field of the network but also retain the features to maintain the nonlinearity of the overall network. The fine transmission image is obtained by refining the coarse transmission image using a guided filter. The atmospheric light value is estimated according to the position and brightness of the pixels in the original hazy image. Second, we use the dehazed images generated by the FT-DCRN dehazing algorithm for 3D reconstruction. An advanced relaxed iterative fine matching based on the structure from motion (ARI-SFM) algorithm is proposed. The ARISFM algorithm, which obtains the fine matching corner pairs and reduces the number of iterations, establishes an accurate one-to-one matching corner relationship. The experimental results show that our FT-DCRN dehazing algorithm improves the accuracy compared to other representative algorithms. In addition, the ARI-SFM algorithm guarantees the precision and improves the efficiency.

    DOI

  • Congestion-aware suspicious object detection system using information-centric networking

    Xin Qi, Toshio Sato, Keping Yu, Zheng Wen, San Hlaing Myint, Yutaka Katsuyama, Kiyohito Tokuda, Takuro Sato

    2021 IEEE 18th Annual Consumer Communications and Networking Conference, CCNC 2021    2021.01

     View Summary

    Deadly diseases and terrorist attacks are greatly threatening human safety, which challenges global security. To address this issue, urban surveillance systems are being applied at a rapid pace with mature but inefficient solutions in large scale networks. When a surveillance network is managing the data generated from multiple edge nodes, it is easy to create congestions due to concentrated data traffic and inefficient data delivery mechanism. In parallel, 5G technology, cope with explosive mobile data traffic growth and massive device connections, can realize a true 'Internet of Everything' and build the social and economical digital transformation. In this paper, in the context of 5G technology, we propose an Information-Centric Networking (ICN) surveillance system based on our designed Suspicious Object Network System (SONS) over the concept of next-generation networking. In this solution, the edge nodes in the network distribute the computing and data storage requirements. We first describe the current surveillance issues and our proposed system architecture. Then we use simulation to verify and evaluate the system performance between legacy all-to-one centralized surveillance system and ICN based decentralized surveillance system.

    DOI

  • Performance evaluation of online machine learning models based on cyclic dynamic and feature-adaptive time series

    Ahmed Salih Al-Khaleefa, Rosilah Hassan, Mohd Riduan Ahmad, Faizan Qamar, Zheng Wen, Azana Hafizah Mohd Aman, Keping Yu

    IEICE Transactions on Information and Systems   E104D ( 8 ) 1172 - 1184  2021

     View Summary

    Machine learning is becoming an attractive topic for researchers and industrial firms in the area of computational intelligence because of its proven effectiveness and performance in resolving real-world problems. However, some challenges such as precise search, intelligent discovery and intelligent learning need to be addressed and solved. One most important challenge is the non-steady performance of various machine learning models during online learning and operation. Online learning is the ability of a machine-learning model to modernize information without retraining the scheme when new information is available. To address this challenge, we evaluate and analyze four widely used online machine learning models: Online Sequential Extreme Learning Machine (OSELM), Feature Adaptive OSELM (FA-OSELM), Knowledge Preserving OSELM (KP-OSELM), and Infinite Term Memory OSELM (ITM-OSELM). Specifically, we provide a testbed for the models by building a framework and configuring various evaluation scenarios given different factors in the topological and mathematical aspects of the models. Furthermore, we generate different characteristics of the time series to be learned. Results prove the real impact of the tested parameters and scenarios on the models. In terms of accuracy, KP-OSELM and ITM-OSELM are superior to OSELM and FA-OSELM. With regard to time efficiency related to the percentage of decreases in active features, ITM-OSELM is superior to KP-OSELM.

    DOI

  • Image super-resolution reconstruction for secure data transmission in Internet of Things environment

    Hongan Li, Qiaoxue Zheng, Wenjing Yan, Ruolin Tao, Xin Qi, Zheng Wen

    Mathematical Biosciences and Engineering   18 ( 5 ) 6652 - 6671  2021  [International journal]

     View Summary

    The image super-resolution reconstruction method can improve the image quality in the Internet of Things (IoT). It improves the data transmission efficiency, and is of great significance to data transmission encryption. Aiming at the problem of low image quality in image super-resolution using neural networks, a self-attention-based image reconstruction method is proposed for secure data transmission in IoT environment. The network model is improved, and the residual network structure and sub-pixel convolution are used to extract the feature of the image. The self-attention module is used extract detailed information in the image. Using generative confrontation method and image feature perception method to improve the image reconstruction effect. The experimental results on the public data set show that the improved network model improves the quality of the reconstructed image and can effectively restore the details of the image.

    DOI PubMed

  • Neural Network-Based Mapping Mining of Image Style Transfer in Big Data Systems

    Hong An Li, Qiaoxue Zheng, Xin Qi, Wenjing Yan, Zheng Wen, Na Li, Chu Tang

    Computational Intelligence and Neuroscience   2021   8387382 - 8387382  2021  [International journal]

     View Summary

    Image style transfer can realize the mutual transfer between different styles of images and is an essential application for big data systems. The use of neural network-based image data mining technology can effectively mine the useful information in the image and improve the utilization rate of information. However, when using the deep learning method to transform the image style, the content information is often lost. To address this problem, this paper introduces L1 loss on the basis of the VGG-19 network to reduce the difference between image style and content and adds perceptual loss to calculate the semantic information of the feature map to improve the model's perceptual ability. Experiments show that the proposal in this paper improves the ability of style transfer, while maintaining image content information. The stylization of the improved model can better meet people's requirements for stylization, and the evaluation indexes of structural similarity, cosine similarity, and mutual information value have increased by 0.323%, 0.094%, and 3.591%, respectively.

    DOI PubMed

  • 3D Remote Healthcare for Noisy CT Images in the Internet of Things Using Edge Computing

    Jing Zhang, Dan Li, Qiaozhi Hua, Xin Qi, Zheng Wen, San Hlaing Myint

    IEEE Access   9   15170 - 15180  2021

     View Summary

    Edge computing can provide many key functions without connecting to centralized servers, which enables remote areas to obtain real-time medical diagnoses. The combination of edge computing and Internet of things (IoT) devices can send remote patient data to the hospital, which will help to more effectively address long-term or chronic diseases. CT images are widely used in the diagnosis of clinical diseases, and their characteristics are an important basis for pathological diagnosis. In the CT imaging process, speckle noise is caused by the interference of ultrasound on human tissues, and its component information is complex. To solve these problems, we propose a 3D reconstruction method for noisy CT images in the IoT using edge computing. First, we propose a multi-stage feature extraction generative adversarial network (MF-GAN) denoising algorithm. The generator of MF-GAN adopts the multi-stage feature extraction, which can ensure the reconstruction of the image texture and edges. Second, we apply the denoised images generated from the MF-GAN method to perform the 3D reconstruction. A marching cube (MC) algorithm based on regional growth and trilinear interpolation (RGT-MC) is proposed. With the idea of regional growth, all voxels containing iso-surfaces are selected and calculated, which accelerates the reconstruction efficiency. The intersection point of the voxel and iso-surface is calculated by the trilinear interpolation algorithm, which effectively improves the reconstruction accuracy. The experimental results show that MF-GAN has a better denoising effect than other algorithms. Compared to other representative 3D algorithms, the RGT-MC algorithm greatly improves the efficiency and precision.

    DOI

  • Communication-Based Book Recommendation in Computational Social Systems

    Long Zuo, Shuo Xiong, Xin Qi, Zheng Wen, Yiwen Tang

    Complexity   2021  2021

     View Summary

    This paper considers current personalized recommendation approaches based on computational social systems and then discusses their advantages and application environments. The most widely used recommendation algorithm, personalized advice based on collaborative filtering, is selected as the primary research focus. Some improvements in its application performance are analyzed. First, for the calculation of user similarity, the introduction of computational social system attributes can help to determine users' neighbors more accurately. Second, computational social system strategies can be adopted to penalize popular items. Third, the network community, identity, and trust can be combined as there is a close relationship. Therefore, this paper proposes a new method that uses a computational social system, including a trust model based on community relationships, to improve the user similarity calculation accuracy to enhance personalized recommendation. Finally, the improved algorithm in this paper is tested on the online reading website dataset. The experimental results show that the enhanced collaborative filtering algorithm performs better than the traditional algorithm.

    DOI

  • A Lightweight Ledger-Based Points Transfer System for Application-Oriented LPWAN

    Keping Yu, Kouichi Shibata, Takanori Tokutake, Rikiya Eguchi, Taiki Kondo, Yusuke Maruyama, Xin Qi, Zheng Wen, Toshio Sato, Yutaka Katsuyama, Kazue Sako, Takuro Sato

    2020 IEEE 6th International Conference on Computer and Communications, ICCC 2020     1972 - 1978  2020.12

     View Summary

    Along with the rapid development of IoT technology, Low power wide area network (LPWAN) has become the primary technology for IoT access today due to its characteristics of low cost, low power consumption, long-distance, and mass connections. At the same time, the points transfer system, as a typical third-party payment application, is attracting more and more extensive attention from academia and industry. Therefore, the research and development of a points transfer system for LPWAN are of great practical importance. However, the current points transfer systems often face problems such as centralization, high requirements on node computing power, and low robustness, which are difficult to adapt to the development of IoT. To address these problems, we propose a lightweight ledger-based points transfer system for application-oriented LPWAN. The system enables the points transfer between tags in LPWAN, where both tags and nodes are limited. Furthermore, it can be utilized even in disaster situations. Experimental results show that our proposed system is intensely robust and has a lower processing time than Bitcoin-like systems to cope with LPWAN's requirement.

    DOI

  • AI-Based W-Band Suspicious Object Detection System for Moving Persons Using GAN: Solutions, Performance Evaluation and Standardization Activities

    Yutaka Katsuyama, Keping Yu, San Hlaing Myint, Toshio Sato, Zheng Wen, Xin Qi

    2020 ITU Kaleidoscope: Industry-Driven Digital Transformation, ITU K 2020    2020.12

     View Summary

    With the intensification of conflicts in different regions, the W-band suspicious object detection system is an essential security means to prevent terrorist attacks and is widely used in many crucial places such as airports. Because artificial intelligence can perform highly reliable and accurate services in the field of image recognition, it is used in suspicious object detection systems to increase the recognition rate for suspicious objects. However, it is challenging to establish a complete suspicious object database, and obtaining sufficient millimeter-wave images of suspicious objects from experiments for AI training is not realistic. To address this issue, this paper verifies the feasibility to generate a large number of millimeter-wave images for AI training by generative adversarial networks. Moreover, we also evaluate the factors that affect the AI recognition rate when the original images used for CNN training are insufficient and how to increase the service quality of AI-based W-band suspicious object detection systems for moving persons. In parallel, all the international standardization organizations have been collectively advancing the novel technologies of AI. We update the reader with information about AI research and standardization related activities in this paper.

    DOI

  • A geometry-based non-stationary wideband mimo channel model and correlation analysis for vehicular communication systems

    Suqin Pang, Fan Bai, Di Zhang, Zheng Wen, Takuro Sato

    Proceedings - 2020 16th International Conference on Mobility, Sensing and Networking, MSN 2020     496 - 501  2020.12

     View Summary

    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.

    DOI

  • Knowledge, attitudes, and practices toward COVID-19 among university students in Japan and associated factors: An online cross-sectional survey

    Asuka Hatabu, Xinhua Mao, Yi Zhou, Norihito Kawashita, Zheng Wen, Mikiko Ueda, Tatsuya Takagi, Yu Shi Tian

    PLoS ONE   15 ( 12 December ) e0244350  2020.12  [International journal]

     View Summary

    The coronavirus disease (COVID-19) pandemic has greatly altered peoples’ daily lives, and it continues spreading as a crucial concern globally. Knowledge, attitudes, and practices (KAP) toward COVID-19 are related to individuals’ adherence to government measures. This study evaluated KAP toward COVID-19 among university students in Japan between May 22 and July 16, 2020, via an online questionnaire, and it further investigated the associated determining KAP factors. Among the eligible respondents (n = 362), 52.8% were female, 79.0% were undergraduate students, 32.9% were students whose major university subjects were biology-related, 35.4% were from the capital region, and 83.7% were Japanese. The overall KAP of university students in Japan was high. All respondents (100%) showed they possessed knowledge on avoiding enclosed spaces, crowded areas, and close situations. Most respondents showed a moderate or higher frequency of washing their hands or wearing masks (both at 96.4%). In addition, 68.5% of respondents showed a positive attitude toward early drug administration. In the logistic regressions, gender, major subjects, education level, nationality, residence, and psychological factors (private self-consciousness and extroversion) were associated with knowledge or attitudes toward COVD-19 (p < 0.05). In the logistic and multiple linear regressions, capital regions, high basic knowledge, high information acquisition, correct information explanations contributed positively to preventative action (p < 0.05). Non-capital regions, male gender, non-bio-backgrounds, high public self-consciousness, high advanced knowledge, incorrect information explanations, and high extroversion contributed negatively to self-restraint (p < 0.05). Moreover, self-restraint was decreasing over time. These findings clarify the Japanese university students’ KAP and the related factors in the early period of the COVID-19 pandemic, and they may help university managers, experts, and policymakers control the future spread of COVID-19 and other emerging infections.

    DOI PubMed

  • Pedestrian positioning in surveillance video using anthropometric properties for effective communication

    Toshio Sato, Xin Qi, Keping Yu, Zheng Wen, San Hlaing Myint, Yutaka Katsuyama, Kiyohito Tokuda, Takuro Sato

    International Symposium on Wireless Personal Multimedia Communications, WPMC   2020-October  2020.10

     View Summary

    Positioning of pedestrians or persons is an important technique for video-based systems. For network surveillance systems, positioning can be applied to reduce data volume for storage devices and communication traffic. In this paper, we propose a simple positioning method using anthropometric properties such as a face length. A foot point in an image is estimated based on face detection results and anthropometric properties, then perspective transformation converts the foot point into a position on the floor plane. We improve the anthropometric model to reduce estimation errors of positioning. Moreover, as an application of pedestrian positioning, we implement data reduction functions of video data for surveillance systems. Experiments using a 4K video indicate that the average positioning error improves to 0.5 m. In terms of data reduction, we found that combination of tracking, selection of key frames, cropping, resizing, and JPEG compression reduce the 35.6 MB video data to 70 kB. These experiments induce that our approach realize simple and precise positioning and data reduction for effective communication for video surveillance systems.

    DOI

  • Radiometric Passive Imaging for Robust Concealed Object Identification

    San Hlaing Myint, Yutaka Katsuyama, Toshio Sato, Xin Qi, Zheng Wen, Keping Yu, Kiyohito Tokuda, Takuro Sato

    IEEE National Radar Conference - Proceedings   2020-September  2020.09

     View Summary

    Artificial Intelligence (AI) based millimeter wave radiometric imaging has become popular in a wide range of public security check systems, such as concealed object detection and identification. However, the low radiometric temperature contrast between small objects and low sensitivity is restricted to some extent. In this paper, an advanced radiometric passive imaging simulation model is proposed to improve the radiometric temperature contrast. This model considers additional noise, such as blur, variation in sensors, noise sources and summation of the number of frames. We establish a comprehensive training dataset that considers the physical characteristics of concealed objects. It can effectively fill the lack of a large database to avoid deteriorating the identification accuracy of AI applications. Moreover, it is also a key solution for improving the robustness of AI based object identification by using a convolutional neural network (CNN). Finally, simulation results are presented and analyzed to validate the proposed comprehensive training dataset and simulation model. Consequently, the proposed simulation model can effectively improve the robustness and accuracy of AI-based concealed object identification.

    DOI

  • PDKSAP : Perfected Double-Key Stealth Address Protocol without Temporary Key Leakage in Blockchain

    Cong Feng, Liang Tan, Huan Xiao, Keping Yu, Xin Qi, Zheng Wen, You Jiang

    2020 IEEE/CIC International Conference on Communications in China, ICCC Workshops 2020     151 - 155  2020.08

     View Summary

    The stealth address protocol is to create a one-time temporary output address of a transaction, hide its real output address, destroy the association between the input address and the real output address to achieve privacy protection for user identities in the transaction. However, the widely used double-key stealth address protocol (DKSAP) requires the sender to transmit the temporary public key along with the transaction, which enables attackers to easily identify stealth and non-stealth transactions and can lead to the loss of some private information. We propose a double-key stealth address protocol without temporary key leakage - PDKSAP by which senders and receivers maintain local transaction record databases to record the number of transactions with other users. Senders and receivers generate a temporary key pair for a transaction based on the number of transactions between them, which prevent leaking the transaction temporary key. Finally, we verify the protocol through experiments.

    DOI

  • Empirical Analysis of Bitcoin network (2016-2020)

    Ajay Kumar, Abhishek Kumar, Pranav Nerurkar, Muhammad Rukunuddin Ghalib, Achyut Shankar, Zheng Wen, Xin Qi

    2020 IEEE/CIC International Conference on Communications in China, ICCC Workshops 2020     96 - 101  2020.08

     View Summary

    Bitcoin system (or Bitcoin) is a peer-to-peer and decentralized payment system that uses cryptocurrency named bitcoins (BTCs) and was released as open-source software in 2009. Bitcoin platform has attracted both social and anti-social elements. On the one hand, it is social as it ensures the exchange of value, maintaining trust in a cooperative, community-driven manner without the need for a trusted third party. At the same time, it is anti-social as it creates hurdles for law enforcement to trace suspicious transactions due to anonymity and privacy. To understand how the social and anti-social tendencies in the user base of Bitcoin affect its evolution, there is a need to analyze the Bitcoin system as a network. The current paper aims to explore the local topology and geometry of the Bitcoin network during its first decade of existence. Bitcoin transaction data from 01 Jan 2016 00:00:00 GMT to 08 May 2020 13:21:33 GMT was processed for this purpose to build a Bitcoin user graph.

    DOI

  • Blockchain-based Content-oriented Surveillance Network

    Xin Qi, Keping Yu, Zheng Wen, San Hlaing Myint, Yutaka Katsuyama, Toshio Sato, Kiyohito Tokuda, Takuro Sato

    IEEE Vehicular Technology Conference   2020-May  2020.05

     View Summary

    For the reason of public security, there are many surveillance actives taken places in either open areas or small areas. During an outburst of public eventuality, it is necessary to surveil public individuals. Based on the great number of populations nowadays, it is critical to propose efficient and secured data delivery network for surveillance networks. There are many different methods to surveil and secure an area, such as cameras and radio wave scanners. The modern surveillance networks are usually based on video content deliveries which consumes much network bandwidth and data security performance. Because it needs to efficiently deliver and protect the data generated by different devices. We propose a content-oriented IoT surveillance network, currently under development, which aims to identify dangerous individuals with various sensors and track the individuals through areas. This paper describes the concept of simulated passive imaging and identifying for conceal objects, various sensors association for person tracking and its traffic volume reduction. The data security in the network uses trust verification concept from blockchain technology. There are simulation and experiment to prove the work valid.

    DOI

  • Blockchain-Empowered Contact Tracing for COVID-19 Using Crypto-Spatiotemporal Information.

    Zheng Wen, Keping Yu, Xin Qi 0002, Toshio Sato, Yutaka Katsuyama, Takuro Sato, Wataru Kameyama, Fumiyuki Kato, Yang Cao 0011, Masatoshi Yoshikawa, Min Luo, Jun Hashimoto

    2020 IEEE International Conference on E-Health Networking, Application and Services, HEALTHCOM 2020     1 - 6  2020

     View Summary

    The pandemic of the COVID-19 [1] has reawakened people that viruses are still the greatest threat to human society. Quarantining the patients and tracking close contacts has been used for hundreds of years in the battle between humans and the plague, which are still useful today. In the information society, we can employ information communications technology (ICT) to suppress the spread of epidemics and lower the epidemic curve. By using spatiotemporal information, we can trace the trajectories of patients and their close contacts. However, spatiotemporal information also involves personal privacy, and it has become a topic of concern about whether people's privacy should be sacrificed for epidemic control. In this paper, we propose a close contact tracing solution based on crypto-spatiotemporal information (CSI). First, the solution encrypts spatiotemporal information to protect personal privacy. Then, it uses a blockchain platform to realize the proof of CSI and uses Intel SGX [2] based trusted execution environment [3] to perform close contact judgment. Finally, it can trace close contacts while protecting personal privacy. The evaluation results indicate that the advantages and efficiency of the proposed scheme are significant.

    DOI

  • Radiometric Passive Imaging for Robust Concealed Object Identification

    San Hlaing Myint, Yutaka Katsuyama, Toshio Sato, Xin Qi, Zheng Wen, Keping Yu, Kiyohito Tokuda, Takuro Sato

    2020 IEEE RADAR CONFERENCE (RADARCONF20)    2020

     View Summary

    Artificial Intelligence (AI) based millimeter wave radiometric imaging has become popular in a wide range of public security check systems, such as concealed object detection and identification. However, the low radiometric temperature contrast between small objects and low sensitivity is restricted to some extent. In this paper, an advanced radiometric passive imaging simulation model is proposed to improve the radiometric temperature contrast. This model considers additional noise, such as blur, variation in sensors, noise sources and summation of the number of frames. We establish a comprehensive training dataset that considers the physical characteristics of concealed objects. It can effectively fill the lack of a large database to avoid deteriorating the identification accuracy of AI applications. Moreover, it is also a key solution for improving the robustness of AI based object identification by using a convolutional neural network (CNN). Finally, simulation results are presented and analyzed to validate the proposed comprehensive training dataset and simulation model. Consequently, the proposed simulation model can effectively improve the robustness and accuracy of AI-based concealed object identification.

  • Design and Performance Evaluation of an AI-Based W-Band Suspicious Object Detection System for Moving Persons in the IoT Paradigm

    Keping Yu, Xin Qi, Toshio Sato, San Hlaing Myint, Zheng Wen, Yutaka Katsuyama, Kiyohito Tokuda, Wataru Kameyama, Takuro Sato

    IEEE Access   8   81378 - 81393  2020

     View Summary

    The threat of terrorism has spread all over the world, and the situation has become grave. Suspicious object detection in the Internet of Things (IoT) is an effective way to respond to global terrorist attacks. The traditional solution requires performing security checks one by one at the entrance of each gate, resulting in bottlenecks and crowding. In the IoT paradigm, it is necessary to be able to perform suspicious object detection on moving people. Artificial intelligence (AI) and millimeter-wave imaging are advanced technologies in the global security field. However, suspicious object detection for moving persons in the IoT, which requires the integration of many different imaging technologies, is still a challenge in both academia and industry. Furthermore, increasing the recognition rate of suspicious objects and controlling network congestion are two main issues for such a suspicious object detection system. In this paper, an AI-based W-band suspicious object detection system for moving persons in the IoT paradigm is designed and implemented. In this system, we establish a suspicious object database to support AI technology for improving the probability of identifying suspicious objects. Moreover, we propose an efficient transmission mechanism to reduce system network congestion since a massive amount of data will be generated by 4K cameras during real-time monitoring. The evaluation results indicate that the advantages and efficiency of the proposed scheme are significant.

    DOI

  • Medical Image Coloring Based on Gabor Filtering for Internet of Medical Things

    Hong An Li, Jiangwen Fan, Keping Yu, Xin Qi, Zheng Wen, Qiaozhi Hua, Min Zhang, Qiaoxue Zheng

    IEEE Access   8   104016 - 104025  2020

     View Summary

    Color medical images better reflect a patient's lesion information and facilitate communication between doctors and patients. The combination of medical image processing and the Internet has been widely used for clinical medicine on Internet of medical things. The classical Welsh method uses matching pixels to achieve color migration of grayscale images, but it exists problems such as unclear boundary and single coloring effect. Therefore, the key information of medical images after coloring can't be reflected efficiently. To address this issue, we propose an image coloring method based on Gabor filtering combined with Welsh coloring and apply it to medical grayscale images. By using Gabor filtering, which is similar to the visual stimulus response of simple cells in the human visual system, filtering in 4 directions and 6 scales is used to stratify the grayscale images and extract local spatial and frequency domain information. In addition, the Welsh coloring method is used to render the image with obvious textural features in the layered image. Our experiments show that the color transboundary problem can be solved effectively after the layered processing. Compared to images without stratification, the coloring results of the processed images are closer to the real image.

    DOI

  • Energy and materials-saving management via deep learning for wastewater treatment plants

    Jianhui Wang, Keyi Wan, Xu Gao, Xuhong Cheng, Yu Shen, Zheng Wen, Usman Tariq, Jalil Piran

    IEEE Access   8   191694 - 191705  2020

     View Summary

    With the increasing public attention on sustainability, conservation of energy and materials has been a general demand for wastewater treatment plants (WWTPs). To meet the demand, efficient optimal management and decision mechanism are expected to reasonably configure resource of energy and materials.In recent years, advanced computational techniques such as neural networks and genetic algorithm provided data-driven solutions to overcome some industrial problems. They work from the perspective of statistical learning, mining invisible latent rules from massive data. This paper proposes energy and materials-saving management via deep learning for WWTPs, using real-world business data of a wastewater treatment plant located in Chongqing, China. Treatment processes are modeled through neural networks, and materials cost that satisfies single indexes can be estimated on this basis. Then, genetic algorithm is selected as the decision scheme to compute overall cost that is able to simultaneously satisfy all the indexes. Empirically, experimental results evaluate that with the proposed management method, total energy and materials cost can be reduced by 10%-15%.

    DOI

  • 3D Reconstruction for Super-Resolution CT Images in the Internet of Health Things Using Deep Learning

    Jing Zhang, Ling Rui Gong, Keping Yu, Xin Qi, Zheng Wen, Qiaozhi Hua, San Hlaing Myint

    IEEE Access   8   121513 - 121525  2020

     View Summary

    The Internet of Health Things (IoHT) enables health devices to connect to the Internet and communicate with each other, which provides the high-accuracy and high-security diagnosis result in the medical area. As essential parts of the IoHT, computed tomography (CT) images help doctors diagnose disease. In the traditional disease diagnosing process, low-resolution medical CT images produce low-accuracy diagnosis results for microlesions. Moreover, CT images can only provide 2D information about organs, and doctors should estimate the 3D shape of a lesion based on experience. To solve these problems, we propose a 3D reconstruction method for secure super-resolution computed tomography (SRCT) images in the IoHT using deep learning. First, we use deep learning to obtain secure SRCT images from low-resolution images in the IoHT. To this end, we adopt a conditional generative adversarial network (CGAN) based on the edge detection loss function (EDLF) in the deep learning process, namely EDLF-CGAN algorithm. In this algorithm, the CGAN is employed to generate SRCT images with luminance and contrast as the input auxiliary conditions, which can improve the accuracy of super-resolution (SR) images. An EDLF is proposed to consider the edge features in the generated SRCT images, which reduces the deformation of generated image. Second, we apply the secure SR images generated from the deep learning method to perform 3D reconstruction. An advanced ray casting 3D reconstruction algorithm that can reduce the number of rays by selecting the appropriate bounding box is proposed. Compared with the traditional algorithm, the proposed ray casting 3D reconstruction algorithm can reduce the time and memory cost. The experimental results show that our EDLF-CGAN has a better SR reconstruction effect than other algorithms via the indicators of the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). In addition, our advanced ray casting 3D reconstruction algorithm greatly improves the efficiency compared with the traditional ray casting algorithm.

    DOI

  • Block Chain Based Internet of Medical Things for Uninterrupted, Ubiquitous, User-Friendly, Unflappable, Unblemished, Unlimited Health Care Services (BC IoMT U6HCS)

    J. Indumathi, Achyut Shankar, Muhammad Rukunuddin Ghalib, J. Gitanjali, Qiaozhi Hua, Zheng Wen, Xin Qi

    IEEE Access   8   216856 - 216872  2020

     View Summary

    The most burning topic of today, calls for a holistic solution that is reliable, secure, privacy preserved, cost effective Cloud storage that can tide over the turbulent conditions of the rapidly budding digital storage technologies. This send an outcry for a devoted solution, in the form of an individualized, patient-centric care - IoMT that augments precise disease identifications, decrease in errors, reduction in costs of care through the support of technology, allows patients to direct health information data to doctors,manage drugs, keep Personal Health Records, caters to remote medical supports Care, provides proactive approach to preserving Good Health, improves and Accelerates Clinician Workflows, empowers extreme connectivity due to better automation and perceptions in the DNA of IoMT functions. But IoMT adoption is like a rose with thorns like constraints of increased administrative costs, deficiency of universal data access, present-day electronic medical records. The BCT is used in the framework to overcome the security issues of IoMT through the use of latest encryptions. Furthermore, this framework harnesses the benefits of Block Chain like reduced cost, speed, automation, immutability, near-impossible loss of data, permanence, removal of intermediaries, decentralization of consensus, legitimate access to health data, data safekeeping, accrual-based imbursement mechanisms, and medical supply chain efficacy. The outcomes in this paper are (i)A systematic investigation of the current IoMT, Block Chain and Cloud Storage in Health Care;(ii) Explore the challenges and necessities for the confluence of Block Chain (BC), Internet of Medical Things (IoMT), Cloud Computing (CC);(iii)Formulate the requirements necessary for the real-time remote Health Care of one-to-one care structure, which, supports the vital functions that are critical to the Patient Centric Health Care;(iv) Design and develop a novel BC IoMT U6 HCS (Block Chain based Internet of Medical Things for Uninterrupted, Ubiquitous, User-friendly, Unflappable, Unblemished, Unlimited Health Care Services) Layered Architecture, to support the vital functions critical for Patient Centric Health Care and (v) Implement and test with the previous established and proven techniques. The integrity of the Layered Architecture is validated with the already existing ones in terms of audit performances. The results from the Layered Architecture are validated and are proven to be competent in achieving safe auditing and surpass the former ones. The technology is in the sprouting phases, it is perilous that affiliates of the Health Care community realize the rudimentary ideas behind Block Chain, and detect its feasible impact on the future of patient centric medical care. Finally, and most importantly, this paper also gives a panoramic view on the current research status, and imminent directions of Secure Internet of Medical Things Using Block Chain.

    DOI

  • On Scheduling Policies with Heavy-Tailed Dynamics in Wireless Queueing Systems

    Shengbo Chen, Lanxue Zhang, Cong Shen, Keping Yu, San Hlaing Myint, Zheng Wen

    IEEE Access   8   32137 - 32149  2020

     View Summary

    This paper takes a system view and studies a wireless queueing system where heavy-tailness may occur both at the traffic arrival and in the form of the multi-user interference. With the rapid development of AI technologies, this heavy-tailed traffic model has become more prevalent in the current network system, such as the file or data size used in the deep learning algorithm. We first re-visit the standard asymmetric queueing system with a mix of heavy-tailed and light-tailed traffic, but under a new variable-rate service model that not only better models the dynamics of the wireless medium but also includes the previous models as special cases. We then focus on the scheduling problem when heavy-tailed interference disrupts the serving link. The performance of queueing policies is investigated during an ON/OFF renewal channel process with heavy-tailed OFF periods, and the expected queue length and the throughput characteristic is studied under the priority as well as max-weight scheduling policies. The results show that the expected queue length of the heavy queue cannot be maintained as finite even under the most favorable priority policy. On the other hand, a priority policy can guarantee the finiteness of an expected queue length for the light queue, but the system is not throughput optimal any longer. It is further shown that no benefit can be provided by the max-weight scheduling policy to the light queue for the queue length behavior in a steady-state, though the system is always throughput optimal.

    DOI

  • 3D Reconstruction for motion blurred images using deep learning-based intelligent systems

    Jing Zhang, Keping Yu, Zheng Wen, Xin Qi, Anup Kumar Paul

    Computers, Materials and Continua   66 ( 2 ) 2087 - 2104  2020

     View Summary

    The 3D reconstruction using deep learning-based intelligent systems can provide great help for measuring an individual's height and shape quickly and accurately through 2D motion-blurred images. Generally, during the acquisition of images in real-time, motion blur, caused by camera shaking or human motion, appears. Deep learning-based intelligent control applied in vision can help us solve the problem. To this end, we propose a 3D reconstruction method for motion-blurred images using deep learning. First, we develop a BF-WGAN algorithm that combines the bilateral filtering (BF) denoising theory with a Wasserstein generative adversarial network (WGAN) to remove motion blur. The bilateral filter denoising algorithm is used to remove the noise and to retain the details of the blurred image. Then, the blurred image and the corresponding sharp image are input into the WGAN. This algorithm distinguishes the motion-blurred image from the corresponding sharp image according to the WGAN loss and perceptual loss functions. Next, we use the deblurred images generated by the BFWGAN algorithm for 3D reconstruction. We propose a threshold optimization random sample consensus (TO-RANSAC) algorithm that can remove the wrong relationship between two views in the 3D reconstructed model relatively accurately. Compared with the traditional RANSAC algorithm, the TO-RANSAC algorithm can adjust the threshold adaptively, which improves the accuracy of the 3D reconstruction results. The experimental results show that our BF-WGAN algorithm has a better deblurring effect and higher efficiency than do other representative algorithms. In addition, the TO-RANSAC algorithm yields a calculation accuracy considerably higher than that of the traditional RANSAC algorithm.

    DOI

  • 5G-Enabled Health Systems: Solutions, Challenges and Future Research Trends

    Di Zhang, Teng Zhang, Yunkai Zhai, Joel J.P.C. Rodrigues, Dalong Zhang, Zheng Wen, Keping Yu, Takuro Sato

    11th Academic Conference ITU Kaleidoscope: ICT for Health: Networks, Standards and Innovation, ITU K 2019    2019.12

     View Summary

    In the literature, Information communication technology (ICT)-assisted health systems have been intensively discussed. However, it has seldom become a reality. This is mainly due to the current wireless technologies' limited transmission rate, few connected devices and high latency. On the contrary, the fifth generation (5G) wireless communications can connect more devices, provide faster transmission rates and a lower latency. In this article, we first introduce the 5G-enabled health systems and our specific implementation in the first affiliated hospital of Zhengzhou University (FAHZZU). Afterwards, the potential challenges and future research trends on demonstrating the 5G-enabled health systems are discussed.

    DOI

  • Content-Oriented Common IoT Platform for Emergency Management Scenarios

    Zheng Wen, Xin Qi, Keping Yu, Jairo Eduardo Lopez, Takuro Sato

    International Symposium on Wireless Personal Multimedia Communications, WPMC   2019-November  2019.11

     View Summary

    With the explosive growth of Internet of Things (IoT) devices, the demand for network systems is increasing rapidly. In terms of bandwidth, security, management, and more, there are many bottlenecks in current network systems. To address the above issues, future network technology, such as information-centric networking, is proposed to provide a good solution for IoT applications. However, new communications technologies need to be implemented with new communications applications. The traditional client/server-based network applications will become one of the bottlenecks in information-centric networking (ICN). In this paper, the work of the Ministry of Internal Affairs and Communications project at Waseda University over the past three years is summarized, and a highly efficient content-oriented common IoT platform for emergency management scenarios is proposed.

    DOI

  • Energy-efficient game-theoretical random access for M2M communications in overlapped cellular networks

    Zhenyu Zhou, Junhao Feng, Yunjian Jia, Shahid Mumtaz, Kazi Mohammed Saidul Huq, Jonathan Rodriguez, Di Zhang

    COMPUTER NETWORKS   129   493 - 501  2017.12  [Refereed]

     View Summary

    The unprecedented growth of machine-to-machine (M2M) devices has brought a heavy burden to traditional cellular networks. In this paper, we focus on the overload problem caused by massive connections of M2M devices in overlapped cellular networks. We formulate the joint base station (BS) selection and power allocation optimization problem for each M2M device as a noncooperative access game. The utility function of each M2M device is described as the success probability of random access weighted by the energy efficiency (EE). We propose an iterative energy-efficient game-theoretical random access algorithm, in which each M2M device searches its optimal strategies in turn until no M2M device is able to improve its individual utility with a unilateral deviation. Numerical results demonstrate that significant performance enhancements on both the delay and energy consumption can be achieved simultaneously. (C) 2017 Elsevier B.V. All rights reserved.

    DOI

  • Performance Analysis of Non-Regenerative Massive-MIMO-NOMA Relay Systems for 5G

    Di Zhang, Yuanwei Liu, Zhiguo Ding, Zhenyu Zhou, Arumugam Nallanathan, Takuro Sato

    IEEE TRANSACTIONS ON COMMUNICATIONS   65 ( 11 ) 4777 - 4790  2017.11  [Refereed]

     View Summary

    The non-regenerative massive multi-input-multi-output (MIMO) non-orthogonal multiple access (NOMA) relay systems are introduced in this paper. The NOMA is invoked with a superposition coding technique at the transmitter and successive interference cancellation (SIC) technique at the receiver. In addition, a maximum mean square error-SIC receiver design is adopted. With the aid of deterministic equivalent and matrix analysis tools, a closed-form expression of the signal to interference plus noise ratio (SINR) is derived. To characterize the performance of the considered systems, closed-form expressions of the capacity and sum rate are further obtained based on the derived SINR expression. Insights from the derived analytical results demonstrate that the ratio between the transmitter antenna number and the relay number is a dominate factor of the system performance. Afterward, the correctness of the derived expressions are verified by the Monte Carlo simulations with numerical results. Simulation results also illustrate that: 1) the transmitter antenna, averaged power value, and user number display the positive correlations on the capacity and sum rate performances, whereas the relay number displays a negative correlation on the performance and 2) the combined massive-MIMO-NOMA scheme is capable of achieving higher capacity performance compared with the conventional MIMO-NOMA, relay-assisted NOMA, and massive-MIMO orthogonal multiple access (OMA) scheme.

    DOI

  • Capacity Analysis of NOMA With mmWave Massive MIMO Systems

    Di Zhang, Zhenyu Zhou, Chen Xu, Yan Zhang, Jonathan Rodriguez, Takuro Sato

    IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS   35 ( 7 ) 1606 - 1618  2017.07  [Refereed]

     View Summary

    Non-orthogonal multiple access (NOMA), millimeter wave (mmWave), and massive multiple-input-multiple-output (MIMO) have been emerging as key technologies for fifth generation mobile communications. However, less studies have been done on combining the three technologies into the converged systems. In addition, how many capacity improvements can be achieved via this combination remains unclear. In this paper, we provide an in-depth capacity analysis for the integrated NOMA-mmWave-massive-MIMO systems. First, a simplified mmWave channel model is introduced by extending the uniform random single-path model with angle of arrival. Afterward, we divide the capacity analysis into the low signal to noise ratio (SNR) and high-SNR regimes based on the dominant factors of signal to interference plus noise ratio. In the noise-dominated low-SNR regime, the capacity analysis is derived by the deterministic equivalent method with the Stieltjes-Shannon transform. In contrast, the statistic and eigenvalue distribution tools are invoked for the capacity analysis in the interference-dominated high-SNR regime. The exact capacity expression and the low-complexity asymptotic capacity expression are derived based on the probability distribution function of the channel eigenvalue. Finally, simulation results validate the theoretical analysis and demonstrate that significant capacity improvements can be achieved by the integrated NOMA-mmWave-massive-MIMO systems.

    DOI

  • Node name routing in information-centric Ad-Hoc network

    Zheng Wen, Di Zhang, Keping Yu, Takuro Sato

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E100A ( 2 ) 680 - 687  2017.02  [Refereed]

     View Summary

    We propose the node name routing (NNR) strategy for information-centric ad-hoc networks based on the named-node networking (3N). This strategy is especially valuable for use in disaster areas because, when the Internet is out of service during a disaster, our strategy can be used to set up a self-organizing network via cell phones or other terminal devices that have a sharing ability, and it does not rely on a base station (BS) or similar providers. Our proposed strategy can solve the multiple-name problem that has arisen in prior 3N proposals, as well as the dead loop problems in both 3N ad-hoc networks and TCP/IP ad-hoc networks. To evaluate the NNR strategy, it is compared with the optimized link state routing protocol (OLSR) and the dynamic source routing (DSR) strategy. Computer-based comprehensive simulations showed that our NNR proposal exhibits a better performance in this environment when all of the users are moving randomly. We further observed that with a growing number of users, our NNR protocol performs better in terms of packet delivery, routing cost, etc.

    DOI

  • One Integrated Energy Efficiency Proposal for 5G IoT Communications

    Di Zhang, Zhenyu Zhou, Shahid Mumtaz, Jonathan Rodriguez, Takuro Sato

    IEEE INTERNET OF THINGS JOURNAL   3 ( 6 ) 1346 - 1354  2016.12  [Refereed]

     View Summary

    To further enhance the energy efficiency (EE) performance of fifth generation (5G) Internet of Things systems, an integrated structure is proposed in this paper. That is, other than prior studies that separately study the wireless and wired parts, the wireless and wired parts are holistically combined together to comprehensively optimize the EE of the whole system. The integrated system structure is introduced beforehand with the proposed unified control center components for better deployment of the select-and-sleep mechanism. In addition, in the wireless part, one cellular partition zooming (CPZ) mechanism is proposed. In contrast, in the wired part, a precaching mechanism is introduced. With these proposals, the proposed system EE performance is investigated. Comprehensive computer-based simulation results demonstrate that the proposed schemes display better EE performance. This is due to the fact that system power consumption is further reduced with these schemes as compared to the prior work.

    DOI

  • Reverse Combinatorial Auction based Resource Allocation in Heterogeneous Software Defined Network with Infrastructure Sharing

    Di Zhang, Zheng Chang, Timo Hamalainen

    2016 IEEE 83RD VEHICULAR TECHNOLOGY CONFERENCE (VTC SPRING)    2016  [Refereed]

     View Summary

    In this paper, resource allocation (RA) problem in heterogeneous Software Defined Network (SDN) with infrastructure sharing platform among multiple network service providers (NSPs) is studied. The considered problem is modeled as a reverse combinatorial auction (R-CA) game, which takes competitiveness and fairness of different NSPs into account. The heterogeneous RA associated with personal QoS requirement problem is optimized by maximizing the social welfare, which is demonstrated to be total system throughput. By exploiting the properties of iterative programming, the resulting non-convex Winner Determination Problem (WDP) is transformed into an equivalent convex optimization problem. The proposed R-CA game is strategy-proof and proved to be with low computational complexity. Simulation results illustrate that with SDN controller sharing environment, the proposed iterative ascending price Vickrey (IA-PV) algorithm converges fast and can obtain nearly optimal system throughput. It is also demonstrated to be robust and can ensure higher fairness and individual profit among different NSPs. With the fairness guaranteed, this infrastructure sharing SDN platform can attract more NSPs to participate, in order to achieve more profit and cost reduction.

  • Integrating Energy Efficiency Mechanism with Components Selection for Massive MIMO Based C-RAN

    Di Zhang, Shahid Mumtaz, Zhenyu Zhou, Takuro Sato

    2016 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC)     74 - 79  2016  [Refereed]

     View Summary

    Based on the Cloud-Radio Access Network (C-RAN) structure and massive Multi-Input Multi-Output (MIMO), we propose one comprehensive system model and give the Energy Efficiency (EE) analysis of this system. The C-RAN structure is amended for better antenna control in massive MIMO based C-RAN system model. Furthermore, system EE optimization problem is modeled from a comprehensive way, and its solution is addressed with a convex optimization method plus an offline decision. In EE analysis, apart from the prior literature, Carrier Capacity (CC), antenna, Radio-Frequency (RF) chain, machine room and also the electron circuits are integrally taken into consideration. A positive correlation is observed between CC and the EE performance prior to the optimal value, after this optimal value, further increase CC has little help to EE enhancement.

  • A Key Management Scheme for Secure Communications of Information Centric Advanced Metering Infrastructure in Smart Grid

    Keping Yu, Mohammad Arifuzzaman, Zheng Wen, Di Zhang, Takuro Sato

    IEEE Transactions on Instrumentation and Measurement   64 ( 8 ) 2072 - 2085  2015.08  [Refereed]

     View Summary

    Advanced metering infrastructure (AMI), as the totality of systems and networks to measure, collect, store, analyze, and use energy usage data, is supposed to be the core component in smart grid. In AMI, there are numerous challenges among which cyber security is a major one that needs to be addressed with priority. The information centric networking (ICN) is a promising architecture for the future Internet that disseminates content based on named data instead of named hosts. The congestion control and self-security can enable more scalable, secure, collaborative, and pervasive networking, these make the ICN a potential network architecture for smart grid. This paper aims to apply the ICN approach on AMI system, which we termed as information centric AMI (ICN-AMI). To the best of our knowledge, this is the first attempt to distribute contents (or requests for contents) based on ICN in AMI system. Moreover, a simulation-based performance evaluation is employed to evaluate the effectiveness of the proposed ICN-AMI approach in traffic control for developing AMI system in smart grid. In addition, we proposed a novel key management scheme (KMS) for a large number of smart meters in this system to ensure confidentiality, integrality, and authentication. To validate the scheme, the security analysis, comparisons are done to demonstrate that the proposed information centric KMS (ICN-KMS) is possible and a promising solution for ICN-AMI system.

    DOI

  • Information centric networking for disaster information sharing services

    Zheng Wen, Di Zhang, Keping Yu, Takuro Sato

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E98A ( 8 ) 1610 - 1617  2015.08  [Refereed]

     View Summary

    Information Centric Networking (ICN) had merits in terms of mobility, security, power consumption and network traffic. When a large-scale disaster occurred, the current communication system might be fragile and the server based network service might be unavailable due to the damages, network congestions, and power failure, etc. In this paper, we proposed an ICN based Disaster Information Sharing Service (DISS) [1], [2] system. DISS could provide robust information sharing service. Users could publish disaster information as a content message with the help of our DISS. In addition, by utilizing DISSïs message naming strategy, users could retrieve disaster information even without a server connection. The ICN based DISS could reduce the probability of network congestion when a large number of simultaneous connections occurring. It could provide server-less service in poor network condition. DISS allows users retrieve disaster information from terminals or ICN nodes. During disasters, sharing information timely and effective could protect people from disaster, ensure peopleïs safety.

    DOI

  • Energy Efficiency Scheme with Cellular Partition Zooming for Massive MIMO Systems

    Di Zhang, Keping Yu, Zhenyu Zhou, Takuro Sato

    2015 IEEE 12TH INTERNATIONAL SYMPOSIUM ON AUTONOMOUS DECENTRALIZED SYSTEMS ISADS 2015     266 - 271  2015  [Refereed]

     View Summary

    Massive Multiple-Input Multiple-Output (Massive MIMO) has been realized as a promising technology element for 5G wireless mobile communications, in which Spectral Efficiency (SE) and Energy Efficiency (EE) are two critical issues. Prior estimates have indicated that 57% energy consumption of cellular system comes from the operator, mostly used to feed the base station (BS). Yet previously, the User Equipment (UE) is focused on while studying the EE issue instead of BS. In this case, in this paper, an EE scheme that focuses on the optimization of BS energy consumption is proposed. Apart from the previous studies, which divides the coverage area by circuit section, the coverage area is divided by fan section with the help of Propagation theory for zoom in or zoom out. In the proposal, transmission model and parameters related to EE is deduced first. Afterwards, the Cellular Partition Zooming (CPZ) scheme is proposed where the BS can zoom in to maintain the coverage area or zoom out to save the energy. Comprehensive simulation results demonstrate that CPZ presents better EE performance with negligible impact on the transmission rate.

    DOI

  • A novel synchronization algorithm for IEEE802.11 TDMA ad hoc network

    Zheng Wen, Ung Heo, Jaeho Choi

    2007 IEEE INTERNATIONAL CONFERENCE ON MOBILE AD-HOC AND SENSOR SYSTEMS, VOLS 1-3     865 - 870  2007  [Refereed]

     View Summary

    Time synchronization problem has been thoroughly studied for years, as it is a critical service for many applications. A novel self-synchronization algorithm is proposed for IEEE802.11 interface in TDMA-based ad hoc network, in which the advantage of RBS is exploited for the leading node election. Here, it overcomes shortcomings of previous methods by adopting a novel and efficient clock updating algorithm. The proposed scheme can be successfully applied to support real time applications such as voice calls over the multi-hop ad hoc network. The preliminary analytical results yields that the maximum clock offset is within 10 mu s.

▼display all

Misc

  • Using linguistic properties of place specification for network naming to improve mobility performance

    Jairo López, Quang Ngoc Nguyen, Zheng Wen, Keping Yu, Takuro Sato

    Sensors (Switzerland)   19 ( 13 )  2019.07  [International journal]

     View Summary

    By considering the definitions and properties from the field of linguistics regarding place specification, a questionnaire that can be used to improve naming in networks is obtained. The questionnaire helps introduce the idea of place specification from linguistics and the concept of metric spaces into network naming schemes. The questionnaire results are used to improve the basic Information-Centric Networking (ICN) architecture’s notoriously lax network naming structure. The improvements are realized by leveraging components from the Named-Node Network Architecture, a minor ICN design, to supply the resulting network architecture with the properties the questionnaire highlights. Evaluation results from experiments demonstrate that modifying the network architecture so that the proposed questionnaire is satisfied results in achieving high mobility performance. Specifically, the proposed system can obtain mean application goodput at above 88% of the ideal result, with a delay below 0.104 s and with the network time-out Interest ratio below 0.082 for the proposed single mobile push producer, single mobile consumer scenario, even when the nodes reach the maximum tested speed of 14 m/s.

    DOI PubMed

  • Content-oriented disaster network utilizing named node routing and field experiment evaluation

    Xin Qi, Zheng Wen, Keping Yu, Kazunori Murata, Kouichi Shibata, Takuro Sato

    IEICE Transactions on Information and Systems   E102D ( 5 ) 988 - 997  2019.05

     View Summary

    Low Power Wide Area Network (LPWAN) is designed for low-bandwidth, low-power, long-distance, large-scale connected IoT applications and realistic for networking in an emergency or restricted situation, so it has been proposed as an attractive communication technology to handle unexpected situations that occur during and/or after a disaster. However, the traditional LPWAN with its default protocol will reduce the communication efficiency in disaster situation because a large number of users will send and receive emergency information result in communication jams and soaring error rates. In this paper, we proposed a LPWAN based decentralized network structure as an extension of our previous Disaster Information Sharing System (DISS). Our network structure is powered by Named Node Networking (3N) which is based on the Information-Centric Networking (ICN). This network structure optimizes the excessive useless packet forwarding and path optimization problems with node name routing (NNR). To verify our proposal, we conduct a field experiment to evaluate the efficiency of packet path forwarding between 3N+LPWA structure and ICN+LPWA structure. Experimental results confirm that the load of the entire data transmission network is significantly reduced after NNR optimized the transmission path.

    DOI

  • A novel base-station selection strategy for cellular vehicle-to-everything (C-V2X) communications

    Qiaozhi Hua, Keping Yu, Zheng Wen, Takuro Sato

    Applied Sciences (Switzerland)   9 ( 3 )  2019.02

     View Summary

    Cellular vehicle-to-everything (C-V2X) communication facilitates the improved safety, comfort, and efficiency of vehicles and mobility by exchanging information between vehicles and other entities. In general, only the macrocell or only the femtocell is the communication infrastructure for C-V2X. Currently, a macro-femtocell network is used as the new C-V2X networking architecture. However, there are two unresolved problems for C-V2X in macro-femtocell networks. Firstly, vehicle mobility requires the frequent switching of connections between different base stations; invalid switching results in worse communication quality. Secondly, unintelligent base station selections cause network congestion and network-load imbalance. To address the above challenges, this paper proposes a base station selection strategy based on a Markov decision policy for a vehicle in a macro-femtocell system. Firstly, we present a mechanism to predict received signal strength (RSS) for base station selection. Secondly, a comparing Markov decision policy algorithm is presented in C-V2X. To the best of our knowledge, this is the first attempt to achieve predicted RSS based on a Markov decision policy in C-V2X technology. To validate the proposed mechanism, we simulated the traditional base station selection and our proposal when the vehicle moved at different speeds. This demonstrates that the effectiveness of a traditional base station selection policy is obvious only at high speeds, and this weakness can be resolved by our proposal. Then, we compare our solution with the traditional base station selection policy. The simulation results show that our solution is effective at switching connections between base stations, and it can effectively prevent the overloading of network resources.

    DOI

  • Design and performance evaluation of content-oriented communication system for iot network: A case study of named node networking for real-Time video streaming system

    Xin Qi, Yuwei Su, Keping Yu, Jingsong Li, Qiaozhi Hua, Zheng Wen, Jairo Lopez, Takuro Sato

    IEEE Access   7   88138 - 88149  2019.01

     View Summary

    Information-Centric Networking (ICN) was born in an era that more and more users are shifting their interests to the content itself rather than the location where contents are stored. This paradigm shift in the usage patterns of the Internet, along with the urgent needs for content naming, pervasive caching, better security, and mobility support, has prompted researchers to consider a radical change to the Internet architecture. However, ICN is still in its infancy and development stage, and many issues still exist and need to be addressed. The common ICN architecture is lacking the host-centric communication ability and difficult to provide seamless mobility in current solutions. To solve this problem, our team had proposed the Named-Node Networking (3N) concept, which not only naming the content but also naming the node and it proved to have better performance of providing seamless mobility in the simulation. However, the previous contributions were limited in the 3N namespace for seamless mobility support in both producer and consumer. In this paper, we have proposed a 3N system which includes 3N naming, data delivery, mobility support, and data security. Moreover, we have created a 3N-based real-Time video streaming system to evaluate data delivery performance and mobility handoff performance. The evaluation result proofs that our system performs better than TCP video streaming in a multi-client situation and a WiFi-based handoff was demonstrated.

    DOI

  • Content-Oriented Surveillance System Based on ICN in Disaster Scenarios

    Koki Okamoto, Toru Mochida, Daichi Nozaki, Zheng Wen, Xin Qi, Takuro Sato

    International Symposium on Wireless Personal Multimedia Communications, WPMC   2018-November   484 - 489  2018.07

     View Summary

    This paper deals with an efficient image object detection method for use in a disaster prevention network that uses information-centric networking (ICN). In ICN for disaster prevention, a large number of surveillance cameras are arranged, and disaster image contents corresponding to the user's requests are distributed directly from the node attached to the surveillance camera. At this time, the name of the content requested by the user does not necessarily match the name of the image acquired by the surveillance camera. In this paper, the content requested by the user is processed and named using natural language processing (NLP). In addition, the image content from the surveillance camera is named using artificial intelligence technology. In this way, a method for improving the hit ratio between users and cameras was established. Furthermore, the volume of the interest packets decreases based on the information which area often occurs disaster. As a result, the network efficiency of ICN can be improved.

    DOI

  • AI Management System to Prevent Accidents in Construction Zones Using 4K Cameras Based on 5G Network

    Daichi Nozaki, Koki Okamoto, Toru Mochida, Xin Qi, Zheng Wen, San Hlaing Myint, Kiyohito Tokuda, Takuro Sato, Kazuhiko Tamesue

    International Symposium on Wireless Personal Multimedia Communications, WPMC   2018-November   462 - 466  2018.07

     View Summary

    Accident prevention for trucks, cranes and work vehicles at construction sites is important. Here, we use high-precision surveillance cameras with 4K cameras as IoT terminals to implement safe workplace environments. In this research, the system transmits photographic images from trucks, cranes, and other construction equipment fitted with 4K cameras at the work site to a database via 5G wireless networks, and uses AI to assess the interactions and movements of workers in the database. We introduce a system that makes it possible to avoid crashes by informing truck and crane drivers, and notifying automatic driving trucks and crane cars of that information. It is conceivable that uplink traffic could become congested due to many vehicles equipped with 4K cameras simultaneously transmitting images over the 5G uplink. Here, as a basic 5G characteristic evaluation, 4K images from trucks or cranes moving at a low speed are transmitted to the database according to moving speed and distance to the 5G terminal connecting the base station and IoT device. Based on the error environment, we report the relation with the error of the system that judges and identifies the surrounding environment using AI when video quality is deteriorated.

    DOI

  • Naming scheme using NLP machine learning method for network weather monitoring system based on ICN

    Toru Mochida, Daichi Nozaki, Koki Okamoto, Xin Qi, Zheng Wen, Takuro Sato, Keping Yu

    International Symposium on Wireless Personal Multimedia Communications, WPMC   2017-December   428 - 434  2018.02

     View Summary

    The market for IoT devices has been expanding rapidly for several years, and many fields are anticipating further demand in the future. However, together with this expansion, increased communication failures are expected, and solutions to prevent them are needed. Here, we aim to solve communication problems using a new network, called the CCN (Contents Centric Networking), which is one of the leading ICN (Information Centric Networking) solutions. Our system was constructed by assuming the case of a weather monitoring IoT application in which large data communications were very likely to occur. In this paper, we propose a technique for distributing meteorological data gathered with a weather observation device and 4K camera by ICN, and caching content with a new Naming scheme using machine learning. x

    DOI

  • An artificial neural network-based distributed information-centric network service

    Zheng Wen, Takuro Sato

    International Symposium on Wireless Personal Multimedia Communications, WPMC   2017-December   453 - 458  2018.02

     View Summary

    Artificial neural networks (ANN) have been widely used in various areas. As a bottleneck, hardware specification affects the efficiency of an ANN. With the development of distributed computing, distributed ANNs show advantages in dealing with huge data. The network bandwidth is a new bottleneck restricting the performance of distributed ANNs. Information-Centric Networking (ICN) [1], as the Next Generation Network (NGN) solution, has shown merits regarding mobility, security, power consumption and network traffic. In this paper, we remodel the architecture of network service using ANNs. We proposed an ANN-Based Distributed Information-Centric Network Service (ANN based DICNS). The distributed nodes are connected like a neural network. When a client utilizes the DICNS, the data flow from the source to the consumer node like the signal traveling from an input layer to an output layer in a neural network. By using an ICN, our proposal can significantly reduce network consumption, and the named data can help the DICNS effectively manage and classify the data.

    DOI

  • Node name routing in information-centric Ad-Hoc network

    Zheng Wen, Di Zhang, Keping Yu, Takuro Sato

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E100A ( 2 ) 680 - 687  2017.02

     View Summary

    We propose the node name routing (NNR) strategy for information-centric ad-hoc networks based on the named-node networking (3N). This strategy is especially valuable for use in disaster areas because, when the Internet is out of service during a disaster, our strategy can be used to set up a self-organizing network via cell phones or other terminal devices that have a sharing ability, and it does not rely on a base station (BS) or similar providers. Our proposed strategy can solve the multiple-name problem that has arisen in prior 3N proposals, as well as the dead loop problems in both 3N ad-hoc networks and TCP/IP ad-hoc networks. To evaluate the NNR strategy, it is compared with the optimized link state routing protocol (OLSR) and the dynamic source routing (DSR) strategy. Computer-based comprehensive simulations showed that our NNR proposal exhibits a better performance in this environment when all of the users are moving randomly. We further observed that with a growing number of users, our NNR protocol performs better in terms of packet delivery, routing cost, etc.

    DOI CiNii

  • A Novel ICN & Drone Based Emergency Information System for Disaster Area (回路とシステム)

    Wen Zheng, Zhang Di, Qi Xin, Yu Keping, Sato Takuro

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報   116 ( 421 ) 47 - 52  2017.01

    CiNii

  • A Novel ICN & Drone Based Emergency Information System for Disaster Area (安全・安心な生活とICT)

    Wen Zheng, Zhang Di, Qi Xin, Yu Keping, Sato Takuro

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報   116 ( 422 ) 47 - 52  2017.01

    CiNii

  • Outage probability analysis of NOMA within massive MIMO systems

    Di Zhang, Keping Yu, Zheng Wen, Takuro Sato

    IEEE Vehicular Technology Conference   2016-July  2016.07

     View Summary

    A Pseudo Double Scattering Channel (PDSC) Matrix assumption is proposed here for the downlink Non- Orthogonal Multiple Access (NOMA) within the massive Multi-Input Multi-Output (MIMO) systems. Afterwards, the outage probability analysis of such a system is investigated. That is, with the aid of random matrix and statistics theories, the Cumulative Probability Distribution (CDF) and also the outage probability performance are addressed. After that, the mathematics derivations obtained here are verified through numerical simulation results, wherein we further find out that with antenna number increasing, the system outage probability performance is reduced.

    DOI

  • B-6-121 3N-SIMULATOR PACKAGE TRANSMISSION ON PHYSICAL NETWORK

    Qi Xin, Zhang Lu, Wen Zheng, Sato Takuro

    Proceedings of the IEICE General Conference   2016 ( 2 )  2016.03

    CiNii

  • Seamless mobility in data aware networking

    Jairo E. López, M. Arifuzzaman, Li Zhu, Zheng Wen, Sato Takuro

    Proceedings of the 2015 ITU Kaleidoscope: Trust in the Information Society, K-2015 - Academic Conference     123 - 129  2016.01

     View Summary

    The underlying networks (of the Internet) have been reworked to make way for new technologies, some serious inefficiencies and security problems have arisen. As a result, over the past years, fundamentally new network designs have taken shape and are being tested. In ITU Recommendation Y.3001 [1], four objectives are identified in line with the requirements for Future Network; one of them is data awareness. In ITU Recommandation Y.3033 [2], the 'Mobility' is addressed as one of the key problem spaces of data aware networking (DAN). This paper proposes Named-Node-Networking (3N), a novel architecture for DAN. We design a simulator (nnnSIM) [3] for evaluating our proposed 3N architecture which is the second major contribution of this paper. The nnnSIM simulator is written in C++ under the ns-3 framework [4] and has been made available as open-source software for the scientific community. Considering the importance of a unique DAN architecture, we propose a study for standardization work in the ITU as an initiative which can lead to its rapid adaptation.

    DOI

  • Content oriented surveillance system based on information-centric network

    Xin Qi, Zheng Wen, Toshitaka Tsuda, Wataru Kameyama, Jiro Katto, Takuro Sato, Kouichi Shibata

    2016 IEEE Globecom Workshops, GC Wkshps 2016 - Proceedings    2016

     View Summary

    Urban surveillance systems are being applied in a rapid pace with mature but inefficient solutions. The inefficiency is revealed with two aspects, too concentrated bandwidth and processing requirement. To solve this problem, we proposed a content oriented surveillance system based on Information-Centric Network. However, we can't simply replace TCP/IP streaming structure with named contents streaming structure because it can't improve the surveillance system's efficiency enough. In this paper, we took the ICN network's profits even further with the named contents. Instead of streaming live video to the central data center and processing multiple data stream in the same time, we have designed the nodes to process the captured raw data and produce objective contents for the central data center. With the extremely size difference in raw data and actual valued contents from it, we could apply the method in investigating area people traffic conditions and even in disaster and anti-terrorism scenarios. There was a field experiment performed to evaluate tourists' densities and dressing habits during winter season of March. The experiment expressed the benefits of our system and compared our method with traditional surveillance systems in saving network bandwidth and functionalities.

    DOI

  • A Study on Datafusion Technology in Smartgrid Network

    Zhou Wei, Wen Zheng, Sato Takuro

    Transaction of the Japan Society for Simulation Technology   8 ( 1 ) 25 - 31  2016

     View Summary

    &amp;nbsp;&amp;nbsp;Recently, miniaturization, low cost and standardization activates of the wireless sensor network technologies has been remarkably advanced, because of advancement of the wireless technologies. Especially smart grid is important application of the wireless sensor network technologies. In the smart grid network, the network congestion occurs caused by huge traffic in real time transmission of energy usage data or environment information data in the house or building. It is required to effectively collect the data and improve the network efficiency. We describes the scheme and the results in this paper since we clarified the efficient data transmission based on data fusion method for the energy usage data using Back Propagation (BP) algorithm with Artificial Neural Network.&lt;br&gt;

    CiNii

  • Information Centric Networking for Disaster Information Sharing Services

    WEN Zheng, ZHANG Di, YU Keping, SATO Takuro

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   98 ( 8 ) 1610 - 1617  2015.08

     View Summary

    Information Centric Networking (ICN) had merits in terms of mobility, security, power consumption and network traffic. When a large-scale disaster occurred, the current communication system might be fragile and the server based network service might be unavailable due to the damages, network congestions, and power failure, etc. In this paper, we proposed an ICN based Disaster Information Sharing Service (DISS) [1], [2] system. DISS could provide robust information sharing service. Users could publish disaster information as a content message with the help of our DISS. In addition, by utilizing DISS&#039;s message naming strategy, users could retrieve disaster information even without a server connection. The ICN based DISS could reduce the probability of network congestion when a large number of simultaneous connections occurring. It could provide server-less service in poor network condition. DISS allows users retrieve disaster information from terminals or ICN nodes. During disasters, sharing information timely and effective could protect people from disaster, ensure people&#039;s safety.

    DOI CiNii

  • B-6-108 ICN based disaster information sharing system

    Zhang Chengcheng, Wen Zheng, Sato Takuro

    Proceedings of the IEICE General Conference   2015 ( 2 )  2015.02

    CiNii

  • BS-3-46 Towards SE and EE in 5G with NOMA and Massive MIMO Technologies(BS-3. Advanced Technologies in the Design, Management and Control for Future Innovative Communication Network)

    Zhang Di, Yu Keping, Wen Zheng, Su Yuwei, Sato Takuro

    Proceedings of the IEICE General Conference   2015 ( 2 ) "S - 95"-"S-96"  2015.02

     View Summary

    In 5G research the spectrum efficiency (SE) and energy efficiency (EE) are two crucial issue. Some scholars propose the Massive Multiple-Input Multiple-Output (Massive MIMO) technology as a essential element to achieve the targets. In addition, the non-orthogonal multiple access (NOMA) and mm Wave technologies are proposed towards SE in 5G. In this paper, apart from the previous studies, we study the EE issue while combining the massive MIMO and NOMA together. Which can take advantage of the NOMA for better SE and antenna selection for better EE performance within the background of massive MIMO in 5G.

    CiNii

  • CCN-AMI: Performance evaluation of content-centric networking approach for advanced metering infrastructure in smart grid

    Keping Yu, Li Zhu, Zheng Wen, Arifuzzaman Mohammad, Zhenyu Zhou, Takuro Sato

    2014 IEEE International Workshop on Applied Measurements for Power Systems, AMPS 2014 - Proceedings     121 - 126  2014.11

     View Summary

    Advanced Metering Infrastructure (AMI), as the totality of systems and networks to measure, collect, store, analyze, and use energy usage data, is supposed to the key component that should be preferentially constructed for smart grid. In the meanwhile, content-centric networking (CCN) is perceived as a promising approach where the content itself becomes the core of communication instead of the address or location in the future internet research. Based on its caching advantage, it is widely believed that CCN can effectively reduce the AMI network bandwidth. This paper aims to apply the CCN approach on AMI system, which is called CCN-AMI. To the best of our knowledge, this is the first attempt to distribute contents or requests based on CCN in AMI system. Moreover, a simulation-based performance evaluation is employed to evaluate the effectiveness of the proposed CCN-AMI approach in traffic control for developing AMI system in smart grid.

    DOI

  • B-6-83 CCN BASED DISASTER INFORMATION SERVICE

    Wen Zheng, Zhu Li, Zhao Zhengge, Sato Takuro

    Proceedings of the IEICE General Conference   2014 ( 2 )  2014.03

    CiNii

  • B-6-84 PCC: Against Cache Pollution in CCN

    Wu Chao, Zhao Zhengge, Wen Zheng, Zhu Li, Shen Yang, Na Yu, Sato Takuro

    Proceedings of the IEICE General Conference   2014 ( 2 )  2014.03

     View Summary

    The content-centric network (CCN) provides a new solution to what future network would be like. By caching named data on routers, CCN intends to realize higher speed and energy efficiency in Internet. In this paper, we propose an against-attack caching strategy-popularity comparing caching (PCC). The basic design concept is based on analysis of contents&#039; popularity. Simulation shows that PCC achieves higher hit ratio than LCE when there is no attack, and outperforms LCD and LCE under attack.

    CiNii

  • B-6-85 CCN Based Proactive Caching Scheme for VOD Service

    Zhao Zhengge, Wen Zheng, Zhu Li, Wu Chao, Shen Yang, Sato Takuro

    Proceedings of the IEICE General Conference   2014 ( 2 )  2014.03

    CiNii

  • B-6-91 Contents hit rate evaluation of proactive cashing utilizing transport systems based on CCN

    Zhu Li, Wen Zheng, Wu Chao, Zhao Zhengge, Shen Yang, Yu Na, Sato Takuro

    Proceedings of the IEICE General Conference   2014 ( 2 )  2014.03

     View Summary

    Content Centric Network(CCN) as one of the next generation networks has the characteristic of cache storage in CCN routers which reduces congestion and latency in backbone network. This characteristic can turn into great advantage in railway scene for the large throughput such as at the train station will cause great pressure on backbone network. In this paper, we propose an content pre-fetching scheme by using CCN for railway information distribution. Simulation show that content pre-fetching scheme has better performance in the aspect of bit ratio by using same cache strategy than original CCN.

    CiNii

  • B-6-92 CCN Based the Optimal Mobile Information and Telecommunications which Utilized the Electric Vehicle

    Shen Yang, Wen Zheng, Zhu Li, Wu Chao, Zhao ZhengGe, Yu Na, Sato Takuro

    Proceedings of the IEICE General Conference   2014 ( 2 )  2014.03

    CiNii

  • CCN Based Pre-fetching Scheme for Disaster Scenario

    Zhu Li, Wen Zheng, Wu Chao, Zhao Zhengge, Shen Yang, Yo Na, Sato Takuro

    Technical report of IEICE. RCS   113 ( 456 ) 511 - 514  2014.03

     View Summary

    This paper presents a Content Centric Network(CCN) scheme for disaster scenario by using modern concept of Information and Communication Technology(ICT) approach. Content centric network as a new network which can push relevant content where needed can use its cache and repository characteristic to reduce congestion and latency in backbone network. In disaster scenario, poor network environment will cause communication obstruction; higher demand for information delivery than usual from both inside and outside of the disaster area will bring great pressure on backbone network. CCN with repositories of pre-fetched contents will utilize its robustness and high performance in cache hit and hop distance to help releasing congestion and throughput pressure in backbone network.

    CiNii

  • Evaluation of PCC in CCN MANET

    Wu Chao, Zhu Li, Zhao Zhengge, Wen Zheng, Sato Takuro

    Technical report of IEICE. RCS   113 ( 456 ) 515 - 519  2014.03

     View Summary

    Content Centric Network (CCN) intends to meet the rapid growth of data delivery demand. The mobile application of CCN poses a hot topic, and Mobile Ad-hoc Network (MANET), which plays a crucial role in information propagation in post-disaster rescue, combat missions and infrastructure-less applied with CCN is suggested to be more efficient. However, situation in the mobile case is different as that of wired. In this paper, we focus on the cache characteristics of mobile CCN device. We propose a novel caching decision policy -- Popularity Compare caching (PCC). Simulation show on limited memory mobile devices, PCC outperforms LCE, and achieves higher hit ratio outperforms LCD and LCE under cache attack.

    CiNii

  • CCN Based Proactive Caching Scheme for VoD Service

    Zhao Zhengge, Wen Zheng, Zhu Li, Wu Chao, Shen Yang, SATO Takuro

    Technical report of IEICE. RCS   113 ( 456 ) 523 - 526  2014.03

     View Summary

    TCP/IP&#039;s host-to-host architecture is proved to be inefficient in content distribution because of a lot of bandwidth waste, but most of the media streaming techniques are based on TCP/IP. Content Centric Networking (CCN) is a next generation network architecture which is targeted to solve the above problem by named content and caching content in router. In this paper, we investigate the current VoD service and CCN architecture, and design an arrangement of CCN routers for VoD service, at last we propose a proactive caching scheme for CCN based VoD service.

    CiNii

  • CCN Based Mobile Disaster Information Sharing System : General Talk(Theory)

    Wen Zheng, Zhu Li, Zhao Zhengge, Wu Chao, Shen Yang, Yu Na, Sato Takuro

    Technical report of IEICE. RCS   113 ( 456 ) 521 - 522  2014.02

     View Summary

    The content-centric networking (CCN) has changed the method of network service design. As the next generation network, the CCN provides significant advantages over previous networking. Nowadays, most webservers still work in terms of client to server (C/S) architecture. When a large scale disaster happens, the C/S architecture will become unstable. In this paper, we proposed a disaster information sharing method based on CCN, Content-oriented network service. The terminals could share and gain information from the CCN routers without webservers. The exchange of information is between the routers and mobile terminals. Even if the connection between CCN routers and Webservers is disconnected, our system may still provide disaster information service for terminals.

    CiNii

  • A Key Management Scheme for Secure Communications of Information Centric Advanced Metering Infrastructure in Smart Grid

    Keping Yu, Di Zhang, Arifuzzaman Mohammad, Nam Hoai Nguyen, Takuro Sato

    2014 INTERNATIONAL CONFERENCE ON POWER SYSTEM TECHNOLOGY (POWERCON)   64   2072 - 2085  2014

     View Summary

    The Advanced Metering Infrastructure (AMI) is the core component in Smart Grid. The cyber security is one of the major concerns and challenges should be prior considered. The Information Centric Networking (ICN) is a promising architecture for the future Internet that disseminates content based on named data instead of named hosts. It will be involved into Smart Grid because its excellent congestion control and self-security can enable more scalable, secure, collaborative and pervasive networking. This paper aims at proposing an Information Centric AMI (ICN-AMI) structure and a novel key management scheme (KMS) for a large number of smart meters (SMs) in this system to ensure confidentiality, integrality and authentication. To validate the scheme, the security analysis, comparisons and NDNsim simulation are done to demonstrate that the proposed ICN-KMS is possible solution for ICN-AMI system.

    DOI

▼display all

Industrial Property Rights

  • FIB検索器、FIB検索方法、及びプログラム

    南 勇貴, 佐藤 拓朗, 文 鄭, 斉 欣

    Patent

    J-GLOBAL

Research Projects

  • Blockchain-empowered Contact Tracing for COVID-19 Using Crypto-spatiotemporal Information

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research Grant-in-Aid for Early-Career Scientists

    Project Year :

    2021.04
    -
    2026.03
     

  • サービスに応じたスライス動的生成・管理機能の実証と標準化を目的とする日欧連携5G移動通信基盤テストベッドの研究開発

    総務省  総務省SCOPE サービスに応じたスライス動的生成・管理機能の実証と標準化を目的とする日欧連携5G移動通信基盤テストベッドの研究開発

    Project Year :

    2016.04
    -
    2019.06
     

  • IoT共通基盤技術の確立実証高効率かつセキュアなIoTデータ収集・配信ネットワーク制御技術の確立

    総務省  総務省 IoT共通基盤技術の確立実証高効率かつセキュアなIoTデータ収集・配信ネットワーク制御技術の確立

    Project Year :

    2017.04
    -
    2019.03
     

  • 止まらない通信網”を活用した命をつなぐ減災推進事業

    総務省  総務省 SCOPE 止まらない通信網”を活用した命をつなぐ減災推進事業

    Project Year :

    2016.04
    -
    2018.03
     

Specific Research

  • Content‐oriented Emergency Information Sharing System

    2020  

     View Summary

    In this research, the proposed&nbsp;Content‐oriented Emergency Information Sharing System was realized and evaluated. The user can publish/retrieve the emergency information by using the ICN-based via information-centric network without any server application. And also the related works, such as ICN-based surveillance technologies, are also developed in this research.The result was published at&nbsp;2021 IEEE 18th Annual Consumer Communications &amp; Networking Conference (CCNC).

 

Syllabus

▼display all