A5060465361- IoT and Edge/Fog Computing
- Caching and Content Delivery
- Recommender Systems and Techniques
- Imbalanced Data Classification Techniques
- Privacy-Preserving Technologies in Data
- Electricity Theft Detection Techniques
- IoT Networks and Protocols
- Brain Tumor Detection and Classification
- Opportunistic and Delay-Tolerant Networks
- Digital Imaging for Blood Diseases
- Protein Hydrolysis and Bioactive Peptides
- Advanced Neural Network Applications
- Phytoestrogen effects and research
- Blockchain Technology Applications and Security
- Human Mobility and Location-Based Analysis
- Anomaly Detection Techniques and Applications
- Vehicular Ad Hoc Networks (VANETs)
- Electrocatalysts for Energy Conversion
- High voltage insulation and dielectric phenomena
- Autonomous Vehicle Technology and Safety
- Electrochemical Analysis and Applications
- Age of Information Optimization
- Financial Distress and Bankruptcy Prediction
- Innovation Diffusion and Forecasting
- Advanced Wireless Communication Technologies
Nanyang Technological University
2024-2025
Chongqing Normal University
2025
Chongqing University
2006-2024
Shanxi Medical University
2024
China Automotive Technology and Research Center
2021-2023
University of Kansas
2021
Research Institute of Natural Gas Technology
2019
Hebei Agricultural University
2017
Guizhou University
2012
Driven by numerous emerging services and applications of mobile devices, multi-access edge computing (MEC) is regarded as a promising technique for massive Internet Things (IoT) with 6G networks to alleviate core network congestion reduce service latency. However, the conventional MEC suffers from infrastructure without cloud server (CS) cooperation multiple servers (ESs), which cannot deal large-scale computation tasks in ultra-dense smart environments. This paper investigates issue...
The Internet of Vehicles connects all vehicles and shares dynamic vehicular data via wireless communications to effectively control improve traffic efficiency. However, due movement, sharing based on conventional cloud computing can hardly realize real-time updates. To address these challenges, artificial intelligence (AI)-empowered mobile/multi-access edge (MEC) has been regarded as a promising technique for intelligently supporting various services applications in proximity vehicles. In...
To support rapidly increasing services and applications from users, multi-tier computing is emerged as a promising system-level architecture by distributing computing/caching/communication/networking capabilities between cloud servers to especially deploying edge at network edges (e.g., base stations). However, due heterogeneous content requests of users high-cost hit manner with direct hits, caching still most serious issue be addressed. In this paper, we investigate the...
Recently, artificial intelligence (AI) is undergoing a sustained success renaissance as it can substantially improve networks' cognitive performance and intelligence, thereby contributing to fully unleashing the potential of big data. Pushing AI frontiers network edge in this context trends has given rise an emerging interdiscipline, namely, (EI). Indeed, EI sink cloud's processing capabilities side, provide real-time response while enabling more intelligent services with high performance....
Mobile edge-cloud computing networks can provide distributed, hierarchical, and fine-grained resources, have become a major goal for future high-performance networks. The key is how to jointly optimize service caching computation offloading. However, the joint offloading problem faces three significant challenges of dynamic tasks, heterogeneous coupled decisions. In this paper, we investigate issue in mobile Specifically, formulate optimization as minimizing long-term average latency, which...
Federated Foundation Models (FedFMs) represent a distributed learning paradigm that fuses general competences of foundation models as well privacy-preserving capabilities federated learning. This combination allows the large and small local domain at remote clients to learn from each other in teacher-student setting. paper provides comprehensive summary ten challenging problems inherent FedFMs, encompassing foundational theory, utilization private data, continual learning, unlearning,...
Under the explosive growth of information available on Web, recommender systems have been used as an effective technology to filter useless and attempt recommend most useful items. The proliferation smart phones, wearable devices other Internet Thing (IoT) has gradually driven many novel emerging services which are latency-sensitive computation-intensive with a higher quality-of-service. such circumstances, data sources contain four key characteristics (i.e., sparsity, heterogeneity,...
Recently, mobile edge computing has received widespread attention, which provides infrastructure via pushing cloud computing, network control, and storage to the edges. To improve resource utilization Quality of Service, we investigate issue task offloading for End-EdgeCloud orchestrated in networks. Particularly, jointly optimize server selection allocation minimize weighted sum average cost. A cost minimization problem is formulated underjoint constraints cache communication/computation...
To support rapidly increasing multimedia services of smart cities, mobile edge computing (MEC) networks can significantly reduce content acquisition latency. However, due to user mobility and the possibility re-association, it is challenging obtain a proper caching association policy. In this article, we investigate issue joint with high in MEC by minimizing latency handover address problem, optimize original mixed time-scale problem two stages: long-time scale short-time association....
Contamination flashover is the ultimate result of creeping discharge polluted insulators. Since there are close ties between contamination and leakage currents, it critical to research current characteristics during entire process. The currents porcelain glass insulators monitored analysed through a number laboratory tests in various cases. goal find that useful for pre-warning flashover. emphasis this paper on root-mean-square values waveforms power spectrum estimation currents. Results...
The localized faults of rolling bearings can be diagnosed by its vibration impulsive signals. However, it is always a challenge to extract the feature under background noise and non-stationary conditions. This paper investigates signals detection single-point defect bearing presents novel data-driven approach based on dictionary learning. To overcome effects harmonic components, we propose an autoregressive-minimum entropy deconvolution model separate deconvolve effect transmission path....
Abstract Chronic diseases are one of the most severe health issues in world, due to their terrible clinical presentations such as long onset cycle, insidious symptoms, and various complications. Recently, machine learning has become a promising technique assist early diagnosis chronic diseases. However, existing works ignore problems feature hiding imbalanced class distribution disease datasets. In this paper, we present universal efficient diagnostic framework alleviate above two for...
With the rapid increase of data in mobile edge computing (MEC) networks, devices (MDs) have been generating many computation-latency-sensitive tasks. As MDs are limited by resources terms storage, computation, and bandwidth, part tasks to be offloaded networks or remote cloud for more efficient processing. Hence, task offloading plays a vital role this scene. Existing works about mainly aim at one-shot rarely consider dependencies In paper, we focus on minimizing maximum delay processing...
With the tremendous growth of mobile data traffic generated by various devices such as smartphones, smartpads and wearable devices, it is necessary for network operators to introduce revolutionary networking techniques, thereby satisfying service requirements users. Recently, edge computing (MEC) has been regarded an effective technique alleviate burden on backhaul networks. In this paper, we investigate issue mobility-aware content caching user association ultra-dense MEC networks...