Results 321 to 330 of about 459,637 (360)

Deep Reinforcement Learning Based Latency Minimization for Mobile Edge Computing With Virtualization in Maritime UAV Communication Network

IEEE Transactions on Vehicular Technology, 2022
The rapid development of maritime activities has led to the emergence of more and more computation-intensive applications. In order to meet the huge demand for wireless communications in maritime environment, mobile edge computing (MEC) is considered as ...
Ying-Ying Liu, Junjie Yan, Xiaohui Zhao
semanticscholar   +1 more source

TCDA: Truthful Combinatorial Double Auctions for Mobile Edge Computing in Industrial Internet of Things

IEEE Transactions on Mobile Computing, 2022
Mobile edge computing (MEC) emerges as an appealing paradigm to provide time-sensitive computing services for industrial Internet of Things (IIoT) applications.
Lianbo Ma, Xueyi Wang, Xingwei Wang, Liang Wang, Ying Shi, Min Huang   +5 more
semanticscholar   +1 more source

Edge server placement in mobile edge computing

Journal of Parallel and Distributed Computing, 2019
Abstract With the rapid increase in the development of the Internet of Things and 5G networks in the smart city context, a large amount of data (i.e., big data) is expected to be generated, resulting in increased latency for the traditional cloud computing paradigm.
Shangguang Wang, Yali Zhao, Ching-Hsien Hsu, Jinlinag Xu, Jie Yuan   +4 more
openaire   +2 more sources

STMGCN: Mobile Edge Computing-Empowered Vessel Trajectory Prediction Using Spatio-Temporal Multigraph Convolutional Network

IEEE Transactions on Industrial Informatics, 2022
The revolutionary advances in machine learning and data mining techniques have contributed greatly to the rapid developments of maritime Internet of Things (IoT).
Ryan Wen Liu, Maohan Liang, Jiangtian Nie, Yanli Yuan, Zehui Xiong, Han Yu, Nadra Guizani   +6 more
semanticscholar   +1 more source

Distributed Machine Learning for Multiuser Mobile Edge Computing Systems

IEEE Journal on Selected Topics in Signal Processing, 2022
In this paper, we investigate a distributed machine learning approach for a multiuser mobile edge computing (MEC) network in a cognitive eavesdropping environment, where multiple secondary devices (SDs) have some tasks with different priorities to be ...
Yinghao Guo, Rui Zhao, Shiwei Lai, Lisheng Fan, Xianfu Lei, G. Karagiannidis   +5 more
semanticscholar   +1 more source

A practical architecture for mobile edge computing

2017 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), 2017
Recently, mobile broadband networks are focused on bringing additional capabilities to the network edge. For instance, Mobile Edge Computing (MEC) brings storage and processing capabilities closer to the mobile user i.e., at the radio access network, in order to deploy services with minimum delay.
Subramanya, Tejas, Goratti, Leonardo, Khan, Shah Nawaz, Kafetzakis, Emmanouil, Giannoulakis, Ioannis, Riggio, Roberto   +5 more
openaire   +3 more sources

Mobile Edge Computing Enabled 5G Health Monitoring for Internet of Medical Things: A Decentralized Game Theoretic Approach

IEEE Journal on Selected Areas in Communications, 2021
The prompt evolution of Internet of Medical Things (IoMT) promotes pervasive in-home health monitoring networks. However, excessive requirements of patients result in insufficient spectrum resources and communication overload. Mobile Edge Computing (MEC)
Zhaolong Ning, Peiran Dong, Xiaojie Wang, Xiping Hu, Lei Guo, Bin Hu, Yi Guo, Tie Qiu, Ricky Y. K. Kwok   +8 more
semanticscholar   +1 more source

Mobile computing at the edge (keynote)

Proceedings of the 1st International Conference on Mobile Software Engineering and Systems, 2014
As sales of mobile devices grow and smartphones and tablets become for many the preferred way of interacting with the Internet, social media and the enterprise, organizations are striving to push content and functionality out to mobile users. However, mobile devices still do not have the computing power and battery life that will allow them to perform ...
openaire   +2 more sources

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, Chessa S, Foschini L, Girolami M   +3 more
openaire   +4 more sources

Learning for Computation Offloading in Mobile Edge Computing

IEEE Transactions on Communications, 2018
Mobile edge computing (MEC) is expected to provide cloud-like capacities for mobile users (MUs) at the edge of wireless networks. However, deploying MEC systems faces many challenges, one of which is to achieve an efficient distributed offloading mechanism for multiple users in time-varying wireless environments.
Thinh Quang Dinh, Quang Duy La, Tony Q. S. Quek, Hyundong Shin   +3 more
openaire   +2 more sources