Mobile edge computing and machine learning in the internet of unmanned aerial vehicles: a survey
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 …
the paradigm of the Internet of UAVs, due to their characteristics of flexibility, mobility, and …
Pervasive AI for IoT applications: A survey on resource-efficient distributed artificial intelligence
Artificial intelligence (AI) has witnessed a substantial breakthrough in a variety of Internet of
Things (IoT) applications and services, spanning from recommendation systems and speech …
Things (IoT) applications and services, spanning from recommendation systems and speech …
Edge-cloud polarization and collaboration: A comprehensive survey for ai
Influenced by the great success of deep learning via cloud computing and the rapid
development of edge chips, research in artificial intelligence (AI) has shifted to both of the …
development of edge chips, research in artificial intelligence (AI) has shifted to both of the …
A resource-constrained and privacy-preserving edge-computing-enabled clinical decision system: A federated reinforcement learning approach
Internet-of-Things-enabled E-health system, which could monitor and collect the personal
health information (PHI), has gradually transformed the clinical treatment to a more …
health information (PHI), has gradually transformed the clinical treatment to a more …
Double deep Q-network based dynamic framing offloading in vehicular edge computing
With the rapid development of Artificial Intelligence (AI) and the Internet of Vehicles (IoV),
there is an increasing demand for deploying various intelligent applications on vehicles …
there is an increasing demand for deploying various intelligent applications on vehicles …
Data, user and power allocations for caching in multi-access edge computing
In the multi-access edge computing (MEC) environment, app vendors' data can be cached
on edge servers to ensure low-latency data retrieval. Massive users can simultaneously …
on edge servers to ensure low-latency data retrieval. Massive users can simultaneously …
EosDNN: An efficient offloading scheme for DNN inference acceleration in local-edge-cloud collaborative environments
With the popularity of mobile devices, intelligent applications, eg, face recognition, intelligent
voice assistant, and gesture recognition, have been widely used in our daily lives. However …
voice assistant, and gesture recognition, have been widely used in our daily lives. However …
C-fdrl: Context-aware privacy-preserving offloading through federated deep reinforcement learning in cloud-enabled IoT
Recently, artificial intelligence approaches are widely suggested to optimize numerous
offloading task-scheduling purposes. However, they confront difficulties in maintaining data …
offloading task-scheduling purposes. However, they confront difficulties in maintaining data …
Throughput maximization of delay-aware DNN inference in edge computing by exploring DNN model partitioning and inference parallelism
Mobile Edge Computing (MEC) has emerged as a promising paradigm catering to
overwhelming explosions of mobile applications, by offloading compute-intensive tasks to …
overwhelming explosions of mobile applications, by offloading compute-intensive tasks to …
Energy or accuracy? Near-optimal user selection and aggregator placement for federated learning in MEC
To unveil the hidden value in the datasets of user equipments (UEs) while preserving user
privacy, federated learning (FL) is emerging as a promising technique to train a machine …
privacy, federated learning (FL) is emerging as a promising technique to train a machine …