Results 301 to 310 of about 459,637 (360)

Heterogeneous Computational Resource Allocation for NOMA: Toward Green Mobile Edge-Computing Systems

IEEE Transactions on Services Computing, 2023
Mobile Edge Computing (MEC) is a viable solution in response to the growing demand for broadband services in the new-generation heterogeneous systems. The dense deployment of small cell networks is a key feature of next-generation radio access networks ...
A. Mohajer, M. S. Daliri, A. Mirzaei, Amir Ziaeddini, Mohammad Nabipour, Maryam Bavaghar   +5 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, Chenglong Dou, Yuan Wu, L. Qian, Bin Lin, Haibo Zhou   +5 more
semanticscholar   +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, Lisheng Fan, Fasheng Zhou, Feng Li, Xianfu Lei, Wei-Qiang Xu, A. Nallanathan   +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, Hao Hu, Xiaojie Wang, Lei Guo, Song Guo, Guoyin Wang, Xinbo Gao   +6 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, Weizhe Zhang, Yan Wang, Qiong Li, Xiaoxiong Zhong, Hongwei Yang, Desheng Wang   +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

Distributed Task Offloading and Resource Purchasing in NOMA-Enabled Mobile Edge Computing: Hierarchical Game Theoretical Approaches

ACM Transactions on Embedded Computing Systems, 2023
As the computing resources and the battery capacity of mobile devices are usually limited, it is a feasible solution to offload the computation-intensive tasks generated by mobile devices to edge servers (ESs) in mobile edge computing (MEC).
Ying Chen, Jie Zhao, Jintao Hu, Shaohua Wan, Jiwei Huang   +4 more
semanticscholar   +1 more source

A Middleware for Mobile Edge Computing

IEEE Cloud Computing, 2017
Telecom operators have recently started to deploy massive computing and storage resources at the very edge of their access networks, hence evolving their infrastructures into large, distributed, and capillary computing environments, capable of placing applications very close to users and terminals and well-suited to effectively fulfill the challenging ...
Carrega A., Repetto M., Gouvas P., Zafeiropoulos A.   +3 more
openaire   +2 more sources

Profit Maximization for Cache-Enabled Vehicular Mobile Edge Computing Networks

IEEE Transactions on Vehicular Technology, 2023
In this paper, we investigate a multiuser cache-enabled vehicular mobile edge computing (MEC) network, where one edge server (ES) has some caching and computing capabilities to assist the task computing from the vehicular users.
Wenqi Zhou, Junjuan Xia, Fasheng Zhou, Lisheng Fan, Xianfu Lei, A. Nallanathan, G. Karagiannidis   +6 more
semanticscholar   +1 more source

OL-EUA: Online User Allocation for NOMA-Based Mobile Edge Computing

IEEE Transactions on Mobile Computing, 2023
Mobile edge computing (MEC) raises a variety of new challenges for app vendors, including the Edge User Allocation (EUA) problem. EUA aims to allocate as many app users as possible in an MEC system to minimum edge servers in the system. In non-orthogonal
Guangming Cui, Qiang He, Xiaoyu Xia, Feifei Chen, Fang Dong, Hai Jin, Yun Yang   +6 more
semanticscholar   +1 more source