AI for next generation computing: Emerging trends and future directions
Autonomic computing investigates how systems can achieve (user) specified “control”
outcomes on their own, without the intervention of a human operator. Autonomic computing …
outcomes on their own, without the intervention of a human operator. Autonomic computing …
Distributed artificial intelligence empowered by end-edge-cloud computing: A survey
As the computing paradigm shifts from cloud computing to end-edge-cloud computing, it
also supports artificial intelligence evolving from a centralized manner to a distributed one …
also supports artificial intelligence evolving from a centralized manner to a distributed one …
AI-based fog and edge computing: A systematic review, taxonomy and future directions
Resource management in computing is a very challenging problem that involves making
sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse …
sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse …
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 …
Socialized learning: A survey of the paradigm shift for edge intelligence in networked systems
Amidst the robust impetus from artificial intelligence (AI) and big data, edge intelligence (EI)
has emerged as a nascent computing paradigm, synthesizing AI with edge computing (EC) …
has emerged as a nascent computing paradigm, synthesizing AI with edge computing (EC) …
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 …
An adaptive DNN inference acceleration framework with end–edge–cloud collaborative computing
Abstract Deep Neural Networks (DNNs) based on intelligent applications have been
intensively deployed on mobile devices. Unfortunately, resource-constrained mobile devices …
intensively deployed on mobile devices. Unfortunately, resource-constrained mobile devices …
A survey on collaborative DNN inference for edge intelligence
WQ Ren, YB Qu, C Dong, YQ **g, 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 …
DNN partition and offloading strategy with improved particle swarm genetic algorithm in VEC
C Li, L Chai, K Jiang, Y Zhang, J Liu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Vehicular edge computing (VEC) is a novel computing paradigm, which is designed to
satisfy the growing computation and communication needs of vehicle systems. With the …
satisfy the growing computation and communication needs of vehicle systems. With the …
Contemporary advances in multi-access edge computing: A survey of fundamentals, architecture, technologies, deployment cases, security, challenges, and directions
With advancements of cloud technologies Multi-Access Edge Computing (MEC) emerged as
a remarkable edge-cloud technology to provide computing facilities to resource-restrained …
a remarkable edge-cloud technology to provide computing facilities to resource-restrained …