Unleashing the power of edge-cloud generative ai in mobile networks: A survey of aigc services
Artificial Intelligence-Generated Content (AIGC) is an automated method for generating,
manipulating, and modifying valuable and diverse data using AI algorithms creatively. This …
manipulating, and modifying valuable and diverse data using AI algorithms creatively. This …
Pushing AI to wireless network edge: An overview on integrated sensing, communication, and computation towards 6G
Pushing artificial intelligence (AI) from central cloud to network edge has reached board
consensus in both industry and academia for materializing the vision of artificial intelligence …
consensus in both industry and academia for materializing the vision of artificial intelligence …
Machine and deep learning for resource allocation in multi-access edge computing: A survey
With the rapid development of Internet-of-Things (IoT) devices and mobile communication
technologies, Multi-access Edge Computing (MEC) has emerged as a promising paradigm …
technologies, Multi-access Edge Computing (MEC) has emerged as a promising paradigm …
Mobility support for millimeter wave communications: Opportunities and challenges
Millimeter-wave (mmWave) communication technology offers a potential and promising
solution to support 5G and B5G wireless networks in dynamic scenarios and applications …
solution to support 5G and B5G wireless networks in dynamic scenarios and applications …
DDPQN: An efficient DNN offloading strategy in local-edge-cloud collaborative environments
With the rapid development of the Internet of Things (IoT) and communication technology,
Deep Neural Network (DNN) applications like computer vision, can now be widely used in …
Deep Neural Network (DNN) applications like computer vision, can now be widely used in …
A survey on collaborative DNN inference for edge intelligence
WQ Ren, YB Qu, C Dong, YQ Jing, H Sun… - Machine Intelligence …, 2023 - Springer
With the vigorous development of artificial intelligence (AI), intelligence applications based
on deep neural networks (DNNs) have changed people's lifestyles and production …
on deep neural networks (DNNs) have changed people's lifestyles and production …
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 …
Multi-exit DNN inference acceleration based on multi-dimensional optimization for edge intelligence
Edge intelligence, as a prospective paradigm for accelerating DNN inference, is mostly
implemented by model partitioning which inevitably incurs the large transmission overhead …
implemented by model partitioning which inevitably incurs the large transmission overhead …
Joint multi-user DNN partitioning and task offloading in mobile edge computing
Mobile edge computing is conducive to artificial intelligence computing near terminals, in
which Deep Neural Networks (DNNs) should be partitioned to allocate tasks partially to the …
which Deep Neural Networks (DNNs) should be partitioned to allocate tasks partially to the …
Resource allocation for multiuser edge inference with batching and early exiting
The deployment of inference services at the network edge, called edge inference, offloads
computation-intensive inference tasks from mobile devices to edge servers, thereby …
computation-intensive inference tasks from mobile devices to edge servers, thereby …