Results 321 to 330 of about 4,602,540 (372)

Privacy-Preserving Federated Learning for Industrial Edge Computing via Hybrid Differential Privacy and Adaptive Compression

IEEE Transactions on Industrial Informatics, 2023
With the continuous improvement of hardware computing power, edge computing of industrial data has been gradually applied. In the past decade, the promotion of edge computing has also greatly improved the efficiency of industrial production.
Bin Jiang, Jianqiang Li, Huihui Wang, H. Song   +3 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

The Computation of Binocular Edges

Perception, 1980
A computational model is described which effects the binocular combination of monocular edge information. The distinctive features of the model are: (i) it identifies edge locations in each monocular field by searching for zero crossings in nonorientated centre-surround convolution profiles; (ii) it selects amongst all possible binocular point-for ...
John P. Frisby, John E. W. Mayhew
openaire   +3 more sources

Efficient Container Assignment and Layer Sequencing in Edge Computing

IEEE Transactions on Services Computing, 2023
Containers are becoming a popular way of running applications in edge computing. Before running the application, the edge node must download the application’s container image consisting of multiple layers.
Jiong Lou, Hao Luo, Zhiqing Tang, Weijia Jia, Wei Zhao   +4 more
semanticscholar   +1 more source

Edge Computing and Sensor-Cloud: Overview, Solutions, and Directions

ACM Computing Surveys, 2023
Sensor-cloud originates from extensive recent applications of wireless sensor networks and cloud computing. To draw a roadmap of the current research activities of the sensor-cloud community, we first investigate the state-of-the-art sensor-cloud ...
Tian Wang, Yuzhu Liang, Xuewei Shen, Xi Zheng, A. Mahmood, Quan Z. Sheng   +5 more
semanticscholar   +1 more source

Deviceless edge computing [PDF]

Proceedings of the 10th ACM International Systems and Storage Conference, 2017
The serverless paradigm has been rapidly adopted by developers of cloud-native applications, mainly because it relieves them from the burden of provisioning, scaling and operating the underlying infrastructure. In this paper, we propose a novel computing paradigm - Deviceless Edge Computing that extends the serverless paradigm to the edge of the ...
Stefan Nastic, Alex Glikson, Schahram Dustdar   +2 more
openaire   +1 more source

Serverless Edge Computing—Where We Are and What Lies Ahead

IEEE Internet Computing, 2023
The edge–cloud continuum combines heterogeneous resources, which are complex to manage. Serverless edge computing is a suitable candidate to manage the continuum by abstracting away the underlying infrastructure, improving developers’ experiences, and ...
Philipp Raith, Stefan Nastic, S. Dustdar, S. Dustdar   +3 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

An Introduction to Edge Computing

2021
With the continuous development of the Internet of Things (IoTs) applications, such as smart cities and intelligent transportation, and the rapid development of location-aware and context-aware services, the number of IoTs equipment connections and data generated demonstrate massive growth trends.
Longxiang Gao, Tom H. Luan, Bruce Gu, Youyang Qu, Yong Xiang   +4 more
openaire   +3 more sources

UAV-Assisted Task Offloading in Vehicular Edge Computing Networks

IEEE Transactions on Mobile Computing
Vehicular edge computing (VEC) provides an effective task offloading paradigm by pushing cloud resources to the vehicular network edges, e.g., road side units (RSUs).
Xingxia Dai, Zhu Xiao, Hongbo Jiang, John C.S. Lui   +3 more
semanticscholar   +1 more source