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Security Offloading Scheduling and Caching Optimization Algorithm in UAV Edge Computing
Mobile edge computing, a prospective wireless communication framework, can contribute to offload a large number of tasks to unmanned aerial vehicle (UAV) mobile edge servers. Besides, the demand for server computational resources increasingly ascends as the volume of processing tasks grows. However, in reality, many devices have similar computing tasks and require the same computing data. Therefor...Show More
Task Offloading and Resource Allocation in UAV-Assisted Vehicle Platoon System
Vehicle platooning is a key application in the realm of smart connected vehicles and autonomous driving technologies, holding significant potential to enhance road utilization and save energy consumption. Simultaneously, within intelligent transportation systems, the limited computing resources of vehicle users themselves fail to meet the computational demands of various new applications. Therefor...Show More
Reinforcement Learning based Edge Offloading Strategy for Port Infrastructure States Monitoring
Jingzhe Wang;Qingqing Pan;Ziqi Liu;I Yunlong Lu;Songgui Chen;Zhufang Kuang;Siyu Lin
2024 IEEE/CIC International Conference on Communications in China (ICCC Workshops)
Year: 2024 | Conference Paper |
It is necessary to establish an edge computing system to provide computing power for latency sensitive monitoring data process task of port infrastructure states monitoring sys-tem. Considering the difference between power supply mode of onshore and offshore edge computing servers in port, an edge computing system architecture for port infrastructure monitoring is designed. The monitoring devices ...Show More
HAT: Task Offloading and Resource Allocation in RIS-Assisted Collaborative Edge Computing
Lin Tan;Songtao Guo;Pengzhan Zhou;Zhufang Kuang;Xianlong Jiao
The problem of joint offloading decisions, resource allocation, and Reconfigurable Intelligent Surface (RIS) beamforming matrices for RIS-Assisted Edge Computing is a challenging issue. In this paper, user tasks can be either executed locally, or offloaded to a collaborative device or edge server with the assistance of the RIS, where RIS elements are grouped and assigned to all users to enable par...Show More
Task Offloading and Trajectory Optimization for Secure Communications in Dynamic User Multi-UAV MEC Systems
With the advantages of high mobility and flexible deployment, Unmanned Aerial Vehicle (UAV) combines with Mobile Edge Computing (MEC) is a promising technology. When dynamic Terminal Users (TUs) offload tasks to UAVs, eavesdroppers may eavesdrop on the channel information. The offloading decisions, trajectory plannings of UAVs and resource allocation with the objective of high-capacity secure comm...Show More
Multi-UAV-Enabled Collaborative Edge Computing: Deployment, Offloading and Resource Optimization
Lin Tan;Songtao Guo;Pengzhan Zhou;Zhufang Kuang;Saiqin Long;Zhetao Li
Unmanned aerial vehicle (UAV) edge computing systems provide easy-to-deploy and low-cost services at those areas with inadequate infrastructure by deploying UAVs as moving edge servers for large-scale users. However, user devices are generally distributed unevenly in a large area, which makes it difficult for existing efforts to cope with this realistic scenario for optimal deployment of UAVs. The...Show More
Energy-Efficient Joint Trajectory and Reflecting Design in IRS-Enabled UAV Edge Computing
IEEE Internet of Things Journal
Cited by: Papers (2)
Intelligent reflecting surface (IRS) enabled unmanned aerial vehicle (UAV) edge computing, a new communication technology, can provide sufficient capacity for edge computing system. However, due to the line-of-sight or the non line of sight of communicating environments will impact transmitting rate or delay, the IRS can be utilized to compensate the channel fading in the IRS-enabled UAV edge comp...Show More
Utility-Aware UAV Deployment and Task Offloading in Multi-UAV Edge Computing Networks
IEEE Internet of Things Journal
Cited by: Papers (5)
Unmanned aerial vehicle (UAV)-enabled mobile-edge computing (MEC) is expected to provide low-latency, ultrareliable, and highly robust network services to improve user service experience. In this article, the UAV deployment, task offloading, and resource allocation problem is investigated in a multi-UAV-enabled MEC system with task-intensive region. UAVs as edge servers to provide computing servic...Show More
Joint Task Offloading Scheduling and Resource Allocation in Air–Ground Cooperation UAV-Enabled Mobile Edge Computing
Unmanned Aerial Vehicles (UAVs) are heavily used in disaster or emergency scenarios. In this paper, we investigate the joint problem of task offloading, task scheduling, transmission power and computing resources allocation, and optimization of UAV deployment location for UAV-enabled Mobile Edge Computing (MEC), considering and highlighting the order of execution and transmission of different task...Show More
Computation Efficiency Maximization in Multi-UAV-Enabled Mobile Edge Computing Systems Based on 3D Deployment Optimization
Xiaoheng Deng;Jiahao Zhao;Zhufang Kuang;Xuechen Chen;Qi Guo;Fengxiao Tang
Unmanned aerial vehicles (UAVs) have been widely devoted to mobile edge computing (MEC) systems that have limited resources to provide high-quality computing and communication services for Internet of Things (IoT) terminals. Energy-efficient computation and resource allocation are key issues for the sustainable operation of the above-mentioned systems. The 3D deployment optimization of multi-UAVs ...Show More
NGCICM: A Novel Deep Learning-Based Method for Predicting circRNA-miRNA Interactions
The circRNAs and miRNAs play an important role in the development of human diseases, and they can be widely used as biomarkers of diseases for disease diagnosis. In particular, circRNAs can act as sponge adsorbers for miRNAs and act together in certain diseases. However, the associations between the vast majority of circRNAs and diseases and between miRNAs and diseases remain unclear. Computationa...Show More
Joint Offloading Decision and Trajectory Design for UAV-Enabled Edge Computing With Task Dependency
In this paper, we investigate the joint problem of task offloading, Unmanned Aerial Vehicle (UAV) trajectory design, and resource allocation for UAV-enabled edge computing, considering and highlighting the dependency among different tasks. The corresponding optimization problem, which is a mixed-integer problem, is formulated. To solve this problem, we propose an iterative method based on Block Co...Show More
Joint Offloading Scheduling and Resource Allocation in Vehicular Edge Computing: A Two Layer Solution
Vehicular Edge Computing (VEC) is a promising paradigm for autonomous driving. It can reduce delay and energy consumption of tasks. The problem of joint task offloading scheduling and resource allocation in VEC is a challenge issue. In this paper, we investigate the problem of joint task offloading, task scheduling, and resource allocation in VEC, and the fast changing channel between a vehicle an...Show More
Energy-Efficient Collaborative Multi-Access Edge Computing via Deep Reinforcement Learning
The joint problem of task offloading, collaborative computing, and resource allocation for multi-access edge computing (MEC) is a challenging issue. In this article, splitting computing tasks at MEC servers through collaboration among MEC servers and a cloud server, we investigate the joint problem of collaborative task offloading and resource allocation. A collaborative task offloading, computing...Show More
GCNPCA: miRNA-Disease Associations Prediction Algorithm Based on Graph Convolutional Neural Networks
A growing number of studies have confirmed the important role of microRNAs (miRNAs) in human diseases and the aberrant expression of miRNAs affects the onset and progression of human diseases. The discovery of disease-associated miRNAs as new biomarkers promote the progress of disease pathology and clinical medicine. However, only a small proportion of miRNA-disease correlations have been validate...Show More
Energy-Efficient Joint Task Offloading and Resource Allocation in OFDMA-Based Collaborative Edge Computing
Mobile edge computing (MEC) is an emergent architecture, which brings computation and storage resources to the edge of mobile network and provides rich services and applications near the end users. The joint problem of task offloading and resource allocation in the multi-user collaborative mobile edge computing network (C-MEC) based on Orthogonal Frequency-Division Multiple Access (OFDMA) is a cha...Show More
MSCNE:Predict miRNA-Disease Associations Using Neural Network Based on Multi-Source Biological Information
The important role of microRNA (miRNA) in human diseases has been confirmed by some studies. However, only using biological experiments has greater blindness, leading to higher experimental costs. In this paper a high-efficiency algorithm based on a variety of biological source information and applying a combination of a convolutional neural network (CNN) feature extractor and an extreme learning ...Show More
Multiuser Computation Offloading and Resource Allocation for Cloud–Edge Heterogeneous Network
IEEE Internet of Things Journal
Cited by: Papers (43)
Cloud–edge heterogeneous network is an emerging technique built on edge infrastructure, which is based on the core of cloud computing technology and edge computing capabilities. The joint problem of computation offloading, cache decision, and resource allocation for cloud–edge heterogeneous network system is a challenging issue. In this article, we investigate the joint problem of computation offl...Show More
Correlation Dimension Based Stability Analysis for Cyber-Physical Systems
Cyber-physical systems (CPSs) realize the automatic control of entities through computing systems and networks. Stability is an important factor in CPS for system upgrading and troubleshooting. Traditional analysis methods focus on simulation and formal analysis, which have two major limitations: first, the current state information of CPS is difficult to obtain; second, most CPS face the state sp...Show More
Energy- and Spectral-Efficiency Tradeoff With $\alpha$-Fairness in Energy Harvesting D2D Communication
Energy Harvesting (EH) technology enables Device-to-Device (D2D) User Equipments (DUEs) to harvest energy from ambient energy, making contributions to green communications and breaking the single battery-powered and the regional limitations of device deployment. The joint problem of energy harvesting and resource allocation in EH-based D2D Communication Networks (EH-DCNs) is a challenge issue. In ...Show More
Routing Algorithm Based on Vehicle Position Analysis for Internet of Vehicles
Lei-Lei Wang;Jin-Song Gui;Xiao-Heng Deng;Feng Zeng;Zhu-Fang Kuang
IEEE Internet of Things Journal
Cited by: Papers (76)
Geographic routing is a research hotspot of the Internet of Vehicles (IoV) and intelligent traffic system (ITS). In practice, the vehicle movement is not only affected by its characteristics and the relationship between the vehicle and position but also affected by some implicit factors. Pointing to this problem, we combine the vehicle moving position probability matrix, the vehicle position assoc...Show More
With the rapid increase of smart mobile devices and the improvement of people’s demand for wireless communication, the insufficient system capacity and shortage of spectrum resources is gradually emerging. The current wireless communication technology is facing enormous challenges. Device-to-Device (D2D) technology has become a key technology in the future 5G network, with its flexible working mod...Show More
Energy Efficient D2D Mode Selection and Resource Allocation in Multiple Cellular Systems
Zhufang Kuang;GongQiang Li;Libang Zhang;Huibin Zhou;Changyun Li;Anfeng Liu
The mode selection and resource allocation are important issues in device-to-device (D2D) communication. There are very little research works considering the joint problem of base station selection and load balance of base station with mode selection and base station selection in multiple BSs cellular systems or heterogeneous cellular systems, which is a challenging issue. In this paper, the joint...Show More
Energy Efficient and Low Delay Partial Offloading Scheduling and Power Allocation for MEC
ICC 2019 - 2019 IEEE International Conference on Communications (ICC)
Year: 2019 | Conference Paper |
Cited by: Papers (15)
Mobile edge computing (MEC) is a promising technique to enhance the computation capacity at the edge of mobile networks. The joint problem of partial offloading decision, offloading scheduling and resource allocation for MEC systems is a challenge issue. In this paper, we investigate the problem of partial offloading scheduling and resource allocation for mobile edge computing systems with multipl...Show More
Partial Offloading Scheduling and Power Allocation for Mobile Edge Computing Systems
IEEE Internet of Things Journal
Cited by: Papers (237)
Mobile edge computing (MEC) is a promising technique to enhance computation capacity at the edge of mobile networks. The joint problem of partial offloading decision, offloading scheduling, and resource allocation for MEC systems is a challenging issue. In this paper, we investigate the joint problem of partial offloading scheduling and resource allocation for MEC systems with multiple independent...Show More
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