A5017137213- IoT and Edge/Fog Computing
- IoT Networks and Protocols
- Advanced Wireless Communication Technologies
- Age of Information Optimization
- Energy Efficient Wireless Sensor Networks
- Advanced MIMO Systems Optimization
- Telecommunications and Broadcasting Technologies
- Advanced Wireless Network Optimization
- Cooperative Communication and Network Coding
- Privacy-Preserving Technologies in Data
- Mobile Crowdsensing and Crowdsourcing
- Advanced Computing and Algorithms
- Functional Brain Connectivity Studies
- Domain Adaptation and Few-Shot Learning
- Context-Aware Activity Recognition Systems
- Advanced Neuroimaging Techniques and Applications
- Wireless Networks and Protocols
- MicroRNA in disease regulation
- IoT-based Smart Home Systems
- Machine Learning and ELM
- Hippo pathway signaling and YAP/TAZ
- Extracellular vesicles in disease
- Blockchain Technology Applications and Security
- Multimodal Machine Learning Applications
- Molecular Communication and Nanonetworks
Purple Mountain Laboratories
2020-2025
Shandong University of Traditional Chinese Medicine
2024
Xi'an University of Technology
2024
Polygon Physics (France)
2023
Tianjin Medical University
2022
University of Chinese Academy of Sciences
2018-2020
Shanghai Institute of Microsystem and Information Technology
2019-2020
Shanghai Institute of Computing Technology
2018-2020
ShanghaiTech University
2018-2020
Shanghai Research Center for Wireless Communications
2018
Abstract The fifth generation (5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities in the process of standardized, such as mass connectivity, ultra-reliability, guaranteed low latency. However, 5G will not meet all requirements future 2030 beyond, sixth (6G) expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level security, etc. To these requirements, 6G rely on new enabling technologies, i.e., air...
Wernicke's concept of 'sejunction' or aberrant associations among specialized brain regions is one the earliest hypotheses attempting to explain myriad symptoms in psychotic disorders. Unbiased data mining all possible brain-wide connections large sets an essential first step localizing these circuits.
Future Internet of Things (IoT) networks enabled with fog computing is promising to achieve lower processing delay and lighter link burden, by effectively offloading the tasks terminal nodes (TNs) nearby (FNs) at network edge. Existing researches for energy consumption in fog-enabled mostly focused on minimization overall consumed task services. However, fair among multiple FNs while maintaining a satisfactory efficiency great significance sustainability IoT networks, especially scenarios...
Fog computing has risen as a promising architecture for future Internet of Things, 5G and embedded artificial intelligence applications with stringent service delay requirements along the cloud to things continuum. For typical fog network consisting heterogeneous nodes (FNs) different resources communication capabilities, how effectively schedule complex computation tasks multiple FNs in neighborhood achieve minimal is fundamental challenge. To tackle this problem, new concept named...
Fog computing has been promoted to support delay-sensitive applications in future Internet of Things (IoT). For a general heterogeneous fog network consisting many dispersive nodes (FNs), it may well happen that some them have tasks process, i.e., task (TNs), and spare resources help the TNs process tasks, helper (HNs). It remains fundamental challenge effectively map multiple or into HNs minimize every task's service delay distributed manner, multitask multihelper (MTMH) problem. The...
By providing shared and flexible communication, computation, storage resources along the cloud-to-things continuum, fog computing has become an attractive technology to support delay-sensitive applications in Internet of Things (IoT) future wireless networks. Consider a typical heterogeneous network consisting different types nodes (FNs), wherein some task (TNs) have computation-intensive tasks, while helper (HNs) spare computation for sharing with their neighboring nodes. In order minimize...
Mobile communication standards were developed for enhancing transmission and network performance by using more radio resources improving spectrum energy efficiency. How to effectively address diverse user requirements guarantee everyone's Quality of Experience (QoE) remains an open problem. The Sixth Generation (6G) mobile systems will solve this problem utilizing heterogenous pervasive intelligence support everyone-centric customized services anywhere anytime. In article, we first coin the...
Sixth-generation (6G) networks are evolving toward new features and order-of-magnitude enhancement of systematic performance metrics compared to the current 5G. In particular, 6G expected achieve extreme connectivity with Tbps-scale data rate, Kbps/Hz-scale spectral efficiency, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mu\mathrm{s}$</tex> , -scale latency. To this end, an original three-layer network architecture is designed realize...
Fog computing (FC) has the potential to process computation-intensive tasks in Industrial Internet of Things (IIoT) systems. In parallel with development FC, non-orthogonal multiple access (NOMA) been recognized as a promising technique significantly improve spectrum efficiency. this paper, NOMA-based FC framework for IIoT systems is considered, where task nodes offload their via NOMA nearby helper execution. We formulate joint scheduling and subcarrier allocation problem, an objective...
A fundamental issue in multiaccess edge computing (MEC) is efficiently offloading multiple tasks to helper nodes (MTMH), i.e., MEC servers. However, most of the existing decentralized schemes do not consider interuser interference or merely adopt time division access (TDMA) as scheme for MTMH heterogeneous scenario, leading a large latency. To address these issues, we propose DOT, novel Decentralized Offloading Tasks orthogonal frequency (OFDMA)-based MEC, minimize sum cost terms energy...
Background: Atherosclerosis occurs mainly at arterial branching points exposed to disturbed blood flow. How MST1 (mammalian sterile 20-like kinase 1), the primary in mechanosensitive Hippo pathway modulates flow induced endothelial cells (ECs) activation and atherosclerosis remains unclear. Methods: To assess role of vivo, mice with EC-specific Mst1 deficiency on ApoE −/− background ( iECKO ) were used an model generated by carotid artery ligation. Mass spectrometry, immunoprecipitation,...
In this paper, we investigate a cost model and the resulted cost-minimization user scheduling problem in multi-tier fog computing networks. For typical network consisting of one control node (FCN), multiple access nodes (FANs) equipments (UEs), how to paid FANs for motivating resources sharing, effectively schedule UEs minimize overall FCN, are still problems be resolved. To solve these problems, unified model, including service delay linear inverse demand dynamic payment scheme, is...
Fog computing is seen as a promising approach to perform computation-intensive and latency-critical applications for mobile devices. Existing results mainly focus on power consumption or delay minimization problems which are both from the perspective of end In this work, we further investigate communication computation resources problem standpoint fog server operators instead. practice, must at first decide how many resources, e.g., bandwidth, units should be deployed in order satisfy...
Fog computing, which shifts functions of clouds to the network edge along cloud-to-things continuum, has risen as a promising architecture for realizing vision smart city. In fog how efficiently map computation tasks into variety heterogeneous nodes (FNs) improve quality service, such low latency and energy consumption, is fundamental challenge. this paper, we investigate task scheduling problem in general multiuser multi-FN hetero- geneous networks. We first show that can be formulated...
Fog computing has been promoted to support delay-sensitive applications in future Internet of Things (IoT) and wireless networks. For a general heterogeneous fog network consisting many dispersive Nodes (FNs) with diverse resources capabilities, some them have tasks process, i.e., Task (TNs), while spare help their neighboring TNs process tasks, Helper (HNs). How effectively map multiple or into HNs minimize every task's service delay distributed manner is fundamental challenge, which key...
Fog computing has risen as an evolving architecture to support delay-sensitive applications in Internet of Things (IoT) and next generation mobile networks. For a typical heterogeneous fog network consisting many nodes, some them have different computation tasks while spare resources, which forms multi-task multi-helper (MTMH) network. How effectively map multiple into helper nodes reduce the service delay is key issue be resolved. To tackle this issue, offloading problem minimizing every...
In this paper, a two-stage intelligent scheduler is proposed to minimize the packet-level delay jitter while guaranteeing bound. Firstly, Lyapunov technology employed transform delay-violation constraint into sequential slot-level queue stability problem. Secondly, hierarchical scheme solve resource allocation between multiple base stations and users, where multi-agent reinforcement learning (MARL) gives user priority number of scheduled packets, underlying allocates resource. Our achieves...
Fog computing shows great potential advantages over legacy cloud in terms of latency and efficiency. While it also poses huge challenges task scheduling resource allocation, which are key to reap the full benefits fog computing. Facing new characteristics computing, distributed allocation algorithms necessary but challenging, will be investigated this paper. To minimize a manner, many-to-one matching game with externalities is formulated for problems networks, considering inter-dependency...