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 …
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 …
Green edge AI: A contemporary survey
Artificial intelligence (AI) technologies have emerged as pivotal enablers across a multitude
of industries, including consumer electronics, healthcare, and manufacturing, largely due to …
of industries, including consumer electronics, healthcare, and manufacturing, largely due to …
FRUIT: A blockchain-based efficient and privacy-preserving quality-aware incentive scheme
Incentive plays an important role in knowledge discovery, as it impels users to provide high-
quality knowledge. To promise incentive schemes with transparency, blockchain technology …
quality knowledge. To promise incentive schemes with transparency, blockchain technology …
Efficient federated learning with spike neural networks for traffic sign recognition
With the gradual popularization of self-driving, it is becoming increasingly important for
vehicles to smartly make the right driving decisions and autonomously obey traffic rules by …
vehicles to smartly make the right driving decisions and autonomously obey traffic rules by …
Communication-efficient and cross-chain empowered federated learning for artificial intelligence of things
Conventional machine learning approaches aggregate all training data in a central server,
which causes massive communication overhead of data transmission and is also vulnerable …
which causes massive communication overhead of data transmission and is also vulnerable …
Burst-aware time-triggered flow scheduling with enhanced multi-CQF in time-sensitive networks
Deterministic transmission guarantee in time-sensitive networks (TSN) relies on queue
models (such as CQF, TAS, ATS) and resource scheduling algorithms. Thanks to its ease of …
models (such as CQF, TAS, ATS) and resource scheduling algorithms. Thanks to its ease of …
Decentralized federated learning: A survey and perspective
Federated learning (FL) has been gaining attention for its ability to share knowledge while
maintaining user data, protecting privacy, increasing learning efficiency, and reducing …
maintaining user data, protecting privacy, increasing learning efficiency, and reducing …
A reinforcement learning-driven brain storm optimisation algorithm for multi-objective energy-efficient distributed assembly no-wait flow shop scheduling problem
F Zhao, X Hu, L Wang, T Xu, N Zhu… - International Journal of …, 2023 - Taylor & Francis
A reinforcement learning-driven brain storm optimisation idea (RLBSO) is proposed in this
paper to solve multi-objective energy-efficient distributed assembly no-wait flow shop …
paper to solve multi-objective energy-efficient distributed assembly no-wait flow shop …
Internet of intelligence: A survey on the enabling technologies, applications, and challenges
The Internet of Intelligence is conceived as an emerging networking paradigm, which will
make intelligence as easy to obtain as information. This paper provides an overview of the …
make intelligence as easy to obtain as information. This paper provides an overview of the …