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QoE‐aware mobile computation offloading in mobile edge computing

Concurrency and Computation: Practice and Experience, 2022
AbstractDue to the rapid development of smart phone utilization, the use of fast response with delay sensitive applications leads to high traffic demands. These issues are not yet fulfill by current researchers. When there is a massive crowd of users gathering in hotspot areas such as, railway stations, corporate centers, and malls requires service ...
Dharmalingam Adhimuga Sivasakthi   +1 more
openaire   +1 more source

Priority-Aware Resource Scheduling for UAV-Mounted Mobile Edge Computing Networks

IEEE Transactions on Vehicular Technology, 2023
In this paper, we investigate the joint impact of task priority and mobile computing service on the mobile edge computing (MEC) networks, in which one unmanned aerial vehicle (UAV) provides mobile computing service to help compute the tasks from users in
Wenqi Zhou   +6 more
semanticscholar   +1 more source

Mobile Edge Computing and Machine Learning in the Internet of Unmanned Aerial Vehicles: A Survey

ACM Computing Surveys, 2023
Unmanned Aerial Vehicles (UAVs) play an important role in the Internet of Things and form the paradigm of the Internet of UAVs, due to their characteristics of flexibility, mobility, and low costs.
Zhaolong Ning   +6 more
semanticscholar   +1 more source

Secure Transmission for Multi-UAV-Assisted Mobile Edge Computing Based on Reinforcement Learning

IEEE Transactions on Network Science and Engineering, 2023
UAV communication has received widespread attention in MEC systems due to its high flexibility and line-of-sight transmission. Users can reduce their local computing pressures and computation delay by offloading tasks to the UAV as an edge server ...
Weidang Lu   +6 more
semanticscholar   +1 more source

Unmanned-Aerial-Vehicle-Aided Integrated Sensing and Computation With Mobile-Edge Computing

IEEE Internet of Things Journal, 2023
Integrated sensing and communication (ISAC), which enables the joint radar sensing and data communications, shows its great potential in many intelligent applications.
Ning Huang   +5 more
semanticscholar   +1 more source

Auction-Based Cluster Federated Learning in Mobile Edge Computing Systems

IEEE Transactions on Parallel and Distributed Systems, 2023
Federated Learning (FL), allowing data owners to conduct model training without sending their raw data to third-party servers, can enhance data privacy in Mobile Edge Computing (MEC) which brings data processing closer to the data sources.
Renhao Lu   +6 more
semanticscholar   +1 more source

Microservice-Oriented Service Placement for Mobile Edge Computing in Sustainable Internet of Vehicles

IEEE transactions on intelligent transportation systems (Print), 2023
The integration of Mobile Edge Computing (MEC) and microservice architecture drives the implementation of the sustainable Internet of Vehicles (IoV). The microservice architecture enables the decomposition of a service into multiple independent, fine ...
Leilei Wang   +4 more
semanticscholar   +1 more source

AoI-Aware Scheduling for Air-Ground Collaborative Mobile Edge Computing

IEEE Transactions on Wireless Communications, 2023
As a way of providing users flexible computing services, networks exist that can make full use of air and ground computing resources. Such networks are called air-ground collaborative mobile edge computing (AGC-MEC) networks.
Zhen Qin   +6 more
semanticscholar   +1 more source

Quantum Particle Swarm Optimization for Task Offloading in Mobile Edge Computing

IEEE Transactions on Industrial Informatics, 2023
Mobile edge computing (MEC) deploys servers on the edge of the mobile network to reduce the data transmission delay between servers and mobile devices, and can meet the computing demand of mobile computing tasks.
Shi Dong, Yuanjun Xia, J. Kamruzzaman
semanticscholar   +1 more source

Enhancing Mobile Edge Computing Architecture with Human-Driven Edge Computing Model

2018 14th International Conference on Intelligent Environments (IE), 2018
In an increasingly interconnected world, mobile and wearable devices, through short range communication interfaces and sensors, become needful tools for collecting and disseminating information in high population density environments. In this context Mobile Crowdsensing (MCS), leveraging people's roaming and their devices' resources, raised the citizen
Belli D   +3 more
openaire   +3 more sources

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