Liu Zhi
Researcher Information
Research Activity Information
Paper
- An adaptive asynchronous federated learning framework for heterogeneous Internet of things
Weidong Zhang; Dongshang Deng; Xuangou Wu; Wei Zhao; Zhi Liu; Tao Zhang; Jiawen Kang; Dusit Niyato
Information Sciences, Elsevier BV, 689, 121458-121458, Sep. 2024, Peer-reviwed
Scientific journal - Asynchronous DRL Based Multi-Hop Task Offloading in RSU-Assisted IoV Networks
Wei Zhao; Yu Cheng; Zhi Liu; Xuangou Wu; Nei Kato
Corresponding, IEEE Transactions on Cognitive Communications and Networking, Institute of Electrical and Electronics Engineers (IEEE), 1-1, Jul. 2024, Peer-reviwed
Scientific journal - EHTA: An Environment-cost-based Heterogeneous Task Allocation in Vehicular Crowdsensing
Yuyang Lu; Xingfu Wang; Ammar Hawbani; Ping Liu; Liang Zhao; Zhi Liu
IEEE Transactions on Mobile Computing, Institute of Electrical and Electronics Engineers (IEEE), 1-14, May 2024, Peer-reviwed
Scientific journal - Power-Efficient Wireless Streaming of Multi-Quality Tiled 360 VR Video in MIMO-OFDMA Systems
Chengjun Guo; Lingzhi Zhao; Ying Cui; Zhi Liu; Derrick Wing Kwan Ng
IEEE Transactions on Wireless Communications, Institute of Electrical and Electronics Engineers (IEEE), 20, 8, 5408-5422, Aug. 2021, Peer-reviwed
Scientific journal - BESURE: Blockchain-Based Cloud-Assisted eHealth System with Secure Data Provenance
Shiyu Li; Yuan Zhang; Chunxiang Xu; Nan Cheng; Zhi Liu; Xuemin Sherman Shen
2021 IEEE/ACM 29th International Symposium on Quality of Service (IWQOS), IEEE, 25 Jun. 2021, Peer-reviwed
International conference proceedings - IMP: Impedance Matching Enhanced Power-Delivered-to-Load Optimization for Magnetic MIMO Wireless Power Transfer System
Wangqiu Zhou; Hao Zhou; Wenxiong Hua; Fengyu Zhou; Xiang Cui; Suhua Tang; Zhi Liu; Xiang-Yang Li
2021 IEEE/ACM 29th International Symposium on Quality of Service (IWQOS), IEEE, 25 Jun. 2021, Peer-reviwed
International conference proceedings - LCL: Light Contactless Low-delay Load Monitoring via Compressive Attentional Multi-label Learning
XiaoYu Wang; Hao Zhou; Nikolaos M. Freris; Wangqiu Zhou; Xing Guo; Zhi Liu; Yusheng Ji; Xiang-Yang Li
2021 IEEE/ACM 29th International Symposium on Quality of Service (IWQOS), IEEE, 25 Jun. 2021, Peer-reviwed
International conference proceedings - A Novel Cost Optimization Strategy for SDN-Enabled UAV-Assisted Vehicular Computation Offloading
Liang Zhao; Kaiqi Yang; Zhiyuan Tan; Xianwei Li; Suraj Sharma; Zhi Liu
IEEE Transactions on Intelligent Transportation Systems, Institute of Electrical and Electronics Engineers (IEEE), 22, 6, 3664-3674, Jun. 2021, Peer-reviwed
Scientific journal - WiONE: One-Shot Learning for Environment-Robust Device-Free User Authentication via Commodity Wi-Fi in Man–Machine System
Yu Gu; Huan Yan; Mianxiong Dong; Meng Wang; Xiang Zhang; Zhi Liu; Fuji Ren
IEEE Transactions on Computational Social Systems, Institute of Electrical and Electronics Engineers (IEEE), 8, 3, 630-642, Jun. 2021, Peer-reviwed
Scientific journal - DRLE: Decentralized Reinforcement Learning at the Edge for Traffic Light Control in the IoV
Pengyuan Zhou; Xianfu Chen; Zhi Liu; Tristan Braud; Pan Hui; Jussi Kangasharju
IEEE Transactions on Intelligent Transportation Systems, Institute of Electrical and Electronics Engineers (IEEE), 22, 4, 2262-2273, Apr. 2021, Peer-reviwed
Scientific journal - 3-D Facial Expression Recognition via Attention-Based Multichannel Data Fusion Network
Yu Gu; Huan Yan; Xiang Zhang; Zhi Liu; Fuji Ren
IEEE Transactions on Instrumentation and Measurement, Institute of Electrical and Electronics Engineers (IEEE), 70, 1-10, 2021, Peer-reviwed
Scientific journal - Age of Information-Aware Resource Management in UAV-Assisted Mobile-Edge Computing Systems
Xianfu Chen; Celimuge Wu; Tao Chen; Zhi Liu; Mehdi Bennis; Yusheng Ji
GLOBECOM 2020 - 2020 IEEE Global Communications Conference, IEEE, Dec. 2020, Peer-reviwed
International conference proceedings, English - Collaborative Learning of Communication Routes in Edge-enabled Multi-access Vehicular Environment
Celimuge Wu; Zhi Liu; Fuqiang Liu; Tsutomu Yoshinaga; Yusheng Ji; Jie Li
IEEE Transactions on Cognitive Communications and Networking, 6, 4, 1155-1165, Dec. 2020, Peer-reviwed
Scientific journal, English - Age of Information Aware Radio Resource Management in Vehicular Networks: A Proactive Deep Reinforcement Learning Perspective
Xianfu Chen; Celimuge Wu; Tao Chen; Honggang Zhang; Zhi Liu; Yan Zhang; Mehdi Bennis
IEEE Transactions on Wireless Communications, Institute of Electrical and Electronics Engineers (IEEE), 19, 4, 2268-2281, Apr. 2020
Scientific journal - Optimal Multi-View Video Transmission in Multiuser Wireless Networks by Exploiting Natural and View Synthesis-Enabled Multicast Opportunities
Wei Xu; Ying Cui; Zhi Liu
IEEE Transactions on Communications, Institute of Electrical and Electronics Engineers (IEEE), 68, 3, 1494-1507, Mar. 2020
Scientific journal - Implementation of video data transmission protocol for a narrow sewer pipe screening system using drifting wireless cameras
Susumu Ishihara; Zhi Liu; Seiya Tachibana; Tomonori Yasuda
International Conference on Information Networking, IEEE Computer Society, 2020-, 384-389, 01 Jan. 2020, Saving the cost for inspecting old sewer pipe is a key issue for keeping cities sustainable. To this end, we have been working on developing a low-cost sewer screening method by drifting small capsules with a camera and a wireless LAN function. We have developed a protocol for transmitting video data recorded by multiple camera-capsules drifting in the same pipe and have been investigating the performance of wireless LAN communication in narrow underground pipes. In this paper, we report the improvement of the video data transfer protocol considering the frame aggregation function of IEEE 802.11n Wireless LAN to improve the reliability, also report the measured performance of IEEE 802.11n in a narrow reinforced concrete sewer pipe.
International conference proceedings, English - Edge-Based V2X communications with big data intelligence
Siri Guleng; Celimuge Wu; Zhi Liu; Xianfu Chen
IEEE Access, Institute of Electrical and Electronics Engineers Inc., 8, 8603-8613, 2020, Vehicular Internet-of-Things applications require an efficient Vehicle-to-Everything (V2X) communication scheme. However, it is particularly challenging to achieve a high throughput and low latency with limited wireless resources in highly dynamic vehicular networks. In this article, we propose a scheme that enhances V2V communications through integration of vehicle edge-based forwarding and learning-based edge selection policy optimization. The proposed scheme has three main characteristics. First, the Hierarchical edge-based preemptive route creation is introduced to create hierarchical edges and conduct efficient packet forwarding as well as route aggregation. Second, Two-stage learning is introduced to select efficient edge nodes using big data driven traffic prediction and reinforcement learning-based edge node selection. Third, Context-aware edge selection is employed to improve the performance of edge-based forwarding in various contexts. We use real traffic big data and realistic vehicular network simulations to evaluate the performance of the proposed scheme and show the advantage over other baseline approaches.
Scientific journal, English - AF-DCGAN: AmplitudeFeature Deep Convolutional GAN for Fingerprint Construction in Indoor Localization System
Qiyue Li; Heng Qu; Zhi Liu; Nana Zhou; Wei Sun; Jie li
IEEE Transactions on Emerging Topics in Computational Intelligence, Oct. 2019, Peer-reviwed - The Evolution of Resource Sharing: From One-Sided Market to Two-Sided Market
Yanru Zhang; Yingjie Zhou; Zhi Liu; Bidushi Barua; Duy H.N. Nguyen
IEEE Wireless Communication, Oct. 2019, Peer-reviwed - The Evolution of Resource Sharing: From One-Sided Market to Two-Sided Market,
Yanru Zhang; Yingjie Zhou; Zhi Liu; Bidushi Barua; Duy H.N. Nguyen
IEEE Wireless Communication, Sep. 2019, Peer-reviwed - SleepGuardian: An RF-based Healthcare System Guarding Your Sleep from Afar
Yu Gu; Yantong Wang; Zhi Liu; Jun Liu; Jie Li
IEEE Network, Sep. 2019, Peer-reviwed - Mining Mobile Intelligence for Wireless Systems: A Deep Neural Network Approach
Han Hu; Zhi Liu; Jianping An
IEEE Computational Intelligence Magazine, Sep. 2019, Peer-reviwed - BeSense: Leveraging WiFi Channel Data and Computational Intelligence for Behavior Analysis
Yu Gu; Xiang Zhang; Zhi Liu; Fuji Ren
IEEE Computational Intelligence Magazine, Sep. 2019, Peer-reviwed - Enhancing the performance of cuckoo search algorithm with Multi-learning strategies
Li Huang; Xiao Zheng; Zhi Liu; Jun Huan
IEICE Transactions on Information and Systems, Sep. 2019, Peer-reviwed - Optimal Resource Allocation for Scalable Mobile Edge Computing
Yunlong Gao; Ying Cui; Xinyun Wang; Zhi Liu
IEEE Communication Letter, Sep. 2019, Peer-reviwed - Joint Optimization of Computing Resources and Data Allocation for Mobile Edge Computing (MEC): An Online Approach
Xun Shao; Go Hasegawa; Noriaki Kamiyama; Zhi Liu; Hiroshi Masui; Yusheng Ji
in Proceedings of 28th International Conference on Computer Communications and Networks (ICCCN 2019), Aug. 2019, Peer-reviwed
International conference proceedings, English - Approximate range emptiness in constant time for IoT data streams over sliding windows
Xiujun Wang; Zhi Liu; Yangzhao Yang; Xun Shao; Yu Gu; Susumu Ishihara
Proceedings - International Conference on Computer Communications and Networks, ICCCN, Institute of Electrical and Electronics Engineers Inc., 2019-, 01 Jul. 2019, Facilitating real-time query over massive IoT data streams becomes increasingly important nowadays, for that it can boost the performances of real-time network services significantly. Let d = e1, e2, , et, represent an IoT data stream, where each element et arrives at time point t. In this paper, we consider the problem of how to support fast range emptiness querying over an IoT data stream δ in sliding window model with a space-efficient data structure, and we denote this problem as the (ϵ, L)-ARE-problem. To be more formally, subjected to the constraint of one-pass scan of stream δ, the main task of the (ϵ, L)-ARE-problem is to design a space-efficient data structure that is capable of always representing W(t, n), which are the n latest elements of stream δ until time point t (i.e., W(t, n) = emax{1,t-n+1}, , et-1, et), and quickly answering an emptiness query of the form W(t, n) n I = φ? , with a false positive rate no larger than e, for any query interval I of length up to L. We design a space-efficient data structure D to solve the (ϵ, L)-ARE-problem and prove that D has constant time cost for querying an interval, inserting a stream element and evicting outdated elements. The efficiency is demonstrated with extensive simulation results as well.
International conference proceedings, English - A Contactless and Fine-Grained Sleep Monitoring System Leveraging WiFi Channel Response
Yu Gu; Chenyu Zhang; Yantong Wang; Zhi Liu; Yusheng Ji; Jie Li
IEEE International Conference on Communications, Institute of Electrical and Electronics Engineers Inc., 2019-, 01 May 2019, How can we effectively log a fine-grained sleep record consisting of still postures and in-place motions for the sleep disorder diagnosis without any specialized hardware? Existing sensor-based or vision-based solutions are either obstructive to use or rely on particular devices. This paper introduces SleepGuardian, a Radio Frequency (RF) based sleep monitoring system leveraging only omnipresent WiFi signals to provide a silent (unobtrusive and free of privacy concerns) yet loyal (finegrained and reliable) logging service. The key to SleepGuardian is to model the energy feature of wireless channel as a Gaussian Mixture Model (GMM) to adaptively recognize motions happened during sleep. We prototype SleepGuardian with off-the-shelf WiFi devices and evaluate it in an office. Experimental results over 11 subjects with several artificial and real periods of sleep demonstrate that SleepGuardian is effective since it achieves 100% overall accuracy (ACC), 0% false negative rate (FNR) and 0.64 s mean absolute error (MAE) on average. Considering that SleepGuardian is compatible with existing WiFi infrastructure, it constitutes a low-cost yet promising solution for sleep monitoring.
International conference proceedings, English - A competitive approximation algorithm for data allocation problem in heterogenous mobile edge computing
Xun Shao; Zhi Liu; Mianxiong Dong; Hiroshi Masui; Yusheng Ji
IEEE Vehicular Technology Conference, Institute of Electrical and Electronics Engineers Inc., 2019-, 01 Apr. 2019, In recent years, the fast development of mobile computing has substantially promoted the mobile edge computing (also known as multi-access edge computing, MEC). Placing content in edges is one of the most important uses of MEC for that it can benefit a variety of service and applications such as video streaming and VR/AR. Currently, most of the existing researches are application specified, and the heterogeneities in data allocating devices and content have not been sufficiently explored. Aiming at developing a general optimal data allocating decision algorithm for MEC, in this work, we carry out in-depth study on the interaction of data allocating and fetching in heterogenous edge computing networks, showing the NP-hardness of the optimal decision problem. We then present polynomial algorithms with (1 - 1/e)-approximation factor. Our algorithms has reasonable performance guarantee with low computation complexity. We verify the proposed approach with analysis and simulations.
International conference proceedings, English - A New DY Con- jugate Gradient Method and Applications to Image Denoising,
Wei Xue; Junhong Ren; Xiao Zheng; Zhi Liu; Yueyong Liang
IEICE Trans- actions on Information and Systems, E101-D, 12, 2984-2990, Mar. 2019, Peer-reviwed - Trajectory Based Incentive Mechanisms for Crowdsourcing Indoor Localization with Privacy Protection
Wei Li; Cheng Zhang; Zhi Liu; Yoshiaki Tanaka
IEEE Access, 54042-54051, Mar. 2019, Peer-reviwed - Optimal Multicast of Tiled 360 VR Video in OFDMA Systems
Chengjun Guo; Ying Cui; Zhi Liu
IEEE Communication Letter, Mar. 2019, Peer-reviwed - Optimal Pricing for Service Provision in Heterogeneous IaaS Cloud Market
Xianwei Li; Bo Gu; Cheng Zhang; Zhi Liu; Kyoko Yamori; Yoshiaki Tanaka
IEICE Transactions on Communications, E102-B, Mar. 2019, Peer-reviwed - EmoSense: Computational Intelligence Driven Emotion Sensing via Wireless Channel Dat
Yu Gu; Yantong Wang; Tao Liu; Yusheng Ji; Zhi Liu; Peng Li; Xiaoyan Wang; Fuji Re
IEEE Transactions on Emerging Topics in Computational Intelligence, Mar. 2019, Peer-reviwed - Mobile Edge Computing for the Internet of Vehicles: Offloading Framework and Job Scheduling
Jingyun Feng; Zhi Liu; Celimuge Wu; Yusheng Ji
IEEE Vehicular Technology Magazine, Institute of Electrical and Electronics Engineers Inc., 14, 1, 28-36, 01 Mar. 2019, As an enabling technology for the Internet of Vehicles (IoV), mobile edge computing (MEC) provides potential solutions for sharing the computation capabilities among vehicles, in addition to other accessible resources. In this article, we first introduce a distributed vehicular edge computing solution named the autonomous vehicular edge (AVE), which makes it possible to share neighboring vehicles' available resources via vehicle-tovehicle (V2V) communications. We then extend this concept to a more general online solution called the hybrid vehicular edge cloud (HVC), which enables the efficient sharing of all accessible computing resources, including roadside units (RSUs) and the cloud, by using multiaccess networks. We also demonstrate the impact of these two decentralized edge computing solutions on the task execution performance. Finally, we discuss several open problems and future research directions.
Scientific journal, English - Near-Optimal Data Structure for Approximate Range Emptiness Problem in Information-Centric Internet of Things
Xiujun Wang; Zhi Liu; Yan Gao; Xiao Zheng; Xianfu Chen; Celimuge Wu
IEEE Access, Institute of Electrical and Electronics Engineers Inc., 7, 21857-21869, 2019, The approximate range emptiness problem requires a memory-efficient data structure D to approximately represent a set S of n distinct elements chosen from a large universe U=0,1,N-1 and answer an emptiness query of the form ' S cap [a
b]= for an interval [a
b] of length L (a,b\\in U), with a false positive rate. The designed D for this problem can be kept in high-speed memory and quickly determine approximately whether a query interval is empty or not. Thus, it is crucial for facilitating online query processing in the information-centric Internet of Things applications, where the IoT data are continuously generated from a large number of resource-constrained sensors or readers and then are processed in networks. However, the existing works on the approximate range emptiness problem only consider the simple case when the set S is static, rendering them unsuitable for the continuously generated IoT data. In this paper, we study the approximate range emptiness problem over sliding windows in the IoT Data streams, denoted by -ARESD-problem, where both insertion and deletion are allowed. We first prove that, given a sliding window size n and an interval length L , the lower bound of memory bits needed in any data structure for ARESD-problem is n2 (nL)+Θ (n). Then, a data structure is proposed and proved to be within a factor of 1.33 of the lower bound. The extensive simulation results demonstrate the advantage of the efficiency of our data structure over the baseline approach.
Scientific journal, English - Accurate Position Estimation of a Drifting Wireless LAN Communication Device in a 200mm-Diameter Small Sewer Pipe.
Yuki Takei; Zhi Liu 0002; Hiroaki Sawano; Susumu Ishihara
33rd International Conference on Information Networking(ICOIN), IEEE, 19-24, 2019
International conference proceedings - Multi-Access Mobile Edge Computing for Internet of Vehicles
Jingyun Feng; Zhi Liu; Celimuge Wu; Yusheng Ji
IEEE Vehicular Technology Magazine, Nov. 2018, Peer-reviwed - Spatial Intelligence toward Trustworthy Vehicular IoT
Celimuge Wu; Zhi Liu; Di Zhang; Tsutomu Yoshinaga; Yusheng Ji
IEEE Communications Magazine, 56, 10, 22-27, Oct. 2018, Peer-reviwed
Scientific journal, English - Optimal Multicast of Tiled 360 VR Video
Chengjun Guo; Ying Cui; Zhi Liu
IEEE Wireless Communication Letter, Aug. 2018, Peer-reviwed - Topology Mapping for Popularity-Aware Video Caching in Content-Centric Network
Zhi Liu; Mianxiong Dong; Susumu Ishihara; Cheng Zhang; Bo Gu; Yusheng Ji; Yoshiaki Tanaka
IEEE International Conference on Communications, Institute of Electrical and Electronics Engineers Inc., 2018-, 27 Jul. 2018, Video caching is one of the most important research issues in Content-Centric Network (CCN) and greatly affects its overall performance. The computational complexity of state-of-the-art optimal caching schemes is high, due to the arbitrary network topologies. In this paper, the popularity-aware video caching in topology-known CCN is studied. The complex arbitrary network typology is mapped into a virtual cascade network topology and a caching scheme is designed in accordance with the transformed virtual network rather than the original network. This scheme is proved optimal, and is with polynomial computational complexity. Simulations are conducted and the results show that the proposed scheme outperforms the existing schemes.
International conference proceedings, English - Spatial Intelligence towards Smart Vehicles
Celimuge Wu; Zhi Liu; Di Zhang; Tsutomu Yoshinaga; Yusheng Ji
IEEE Communication Magazine, Jul. 2018, Peer-reviwed - Sleepy: Adaptive sleep monitoring from afar with commodity WiFi infrastructures
Yu Gu; Jinhai Zhan; Zhi Liu; Jie Li; Yusheng Ji; Xiaoyan Wang
IEEE Wireless Communications and Networking Conference, WCNC, Institute of Electrical and Electronics Engineers Inc., 2018-, 1-5, 08 Jun. 2018, Sleep is a major event of our daily lives. Its quality constitutes a critical indicator of people's health conditions, both mentally and physically. Existing sleep monitoring systems either are obstructive to use or fail to provide adequate coverage. To overcome these shortages, we propose Sleepy, an adaptive and noninvasive sleep monitoring system leveraging channel response in the commercial WiFi devices. Sleepy needs no calibrations or target-dependent training to recognize posture changes during sleep. To achieve that, a Gaussian Mixture Model (GMM) based foreground extraction method has been designed to adaptively distinguish motions like rollovers (foreground) from background (stationary postures). We prototype Sleepy and evaluate it in two real environments. In the short-term controlled experiments, Sleepy achieves 95.04% detection accuracy and 4.07% false negative rate. In the 60-minute real sleep studies, Sleepy demonstrates strong stability. Considering that Sleepy is compatible with existing WiFi infrastructures, it constitutes a low-cost yet promising solution for sleep monitoring.
International conference proceedings, English - Resource allocation for SVC streaming over cooperative vehicular networks
Hao Zhou; Xiaoyan Wang; Zhi Liu; Shigeki Yamada; Yusheng Ji
IEEE Transactions on Vehicular Technology, Jun. 2018, Peer-reviwed - Effect of channel bonding and parallel data transmission with IEEE802.11n wireless LAN in a small sewer pipe
Yuki Takei; Zhi Liu; Susumu Ishihara
International Conference on Information Networking, IEEE Computer Society, 2018-, 223-228, 19 Apr. 2018, Sewer pipe deterioration is one serious issue in many countries and sewer pipe inspections are essential for maintaining sewer systems. There are various sewer inspection methods such as visual check, boat-type video cameras, remote robots with or without wired connection. They, however, suffer from many problems such as high labor, monetary cost of robots, long waiting time when using boat-type video cameras. Towards a low-cost, safe, and near real-time inspection of sewer pipe, we have proposed a drifting wireless camera/sensor nodes-based inspection method and identified the radio communication range in a small sewer pipe (200 mm diameter) with off-the-shelf 2.4 GHz and 5 GHz IEEE 802.11b/g wireless LAN devices. In this paper, we investigated the effect of channel bonding introduced by IEEE802.11n and parallel data transmissions using multiple interfaces on improving the performance of wireless communication in small pipes. Measurement results revealed that can be achieved by using channel bonding when the communication distance is less than 4 m and placement of antennas is essential for ensuring a wider communication range. We also discuss a strategy for transmission between an access point and a camera/sensor node moves in small pipes.
International conference proceedings, English
Books and other publications
Research Themes
- Context-aware, Resource Requirement-based Wireless Access Network Densification
Ji Yusheng
Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research, National Institute of Informatics, Grant-in-Aid for Scientific Research (B), The purpose of this research project is by exploring context-aware, resource requirement-driven network densification to realize ultra-high capacity and massive access capability for next-generation wireless access networks. To this end, we have tackled on the resource management and inter-cell interference mitigation problems in heterogeneous wireless cellular networks, and proposed optimization algorithms for dynamic cell-range expansion, users' cell selection, and dynamic network clustering with base station sleeping and shared caching functions. We have also studied on online resource management algorithms for mobile edge computing to provide computing and data caching capabilities in wireless access networks. By leveraging reinforcement learning and fussy logic based techniques, we have also proposed low-overhead clustering based routing protocols for context-aware data delivering in vehicular networks utilizing multiple wireless access technologies., 16H02817
01 Apr. 2016 - 31 Mar. 2019
