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) …
Computation offloading method using stochastic games for software-defined-network-based multiagent mobile edge computing
G Wu, H Wang, H Zhang, Y Zhao… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
In the scenario of Industry 4.0, mobile smart devices (SDs) on production lines have to
process massive amounts of data. These computing tasks sometimes far exceed the …
process massive amounts of data. These computing tasks sometimes far exceed the …
Deep reinforcement learning‐based resource allocation in multi‐access edge computing
Network architects and engineers face challenges in meeting the increasing complexity and
low‐latency requirements of various services. To tackle these challenges, multi‐access …
low‐latency requirements of various services. To tackle these challenges, multi‐access …
Multi-objective optimization for UAV swarm-assisted IoT with virtual antenna arrays
Unmanned aerial vehicle (UAV) network is a promising technology for assisting Internet-of-
Things (IoT), where a UAV can use its limited service coverage to harvest and disseminate …
Things (IoT), where a UAV can use its limited service coverage to harvest and disseminate …
Joint task offloading and resource allocation in aerial-terrestrial UAV networks with edge and fog computing for post-disaster rescue
Unmanned aerial vehicles (UAVs) are playing an increasingly important role in assisting fast-
response post-disaster rescue due to their fast deployment, flexible mobility, and low cost …
response post-disaster rescue due to their fast deployment, flexible mobility, and low cost …
Stackelberg game-based dependency-aware task offloading and resource pricing in vehicular edge networks
L Zhao, S Huang, D Meng, B Liu, Q Zuo… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
Vehicular edge computing (VEC) is an effective paradigm in Internet of Vehicles (IoV), which
allows vehicles to offload delay-sensitive tasks to nearby road side units (RSUs) for …
allows vehicles to offload delay-sensitive tasks to nearby road side units (RSUs) for …
A survey of state-of-the-art on edge computing: Theoretical models, technologies, directions, and development paths
B Liu, Z Luo, H Chen, C Li - IEEE Access, 2022 - ieeexplore.ieee.org
In order to describe the roadmap of current edge computing research activities, we first
address a brief overview of the most advanced edge computing surveys published in the last …
address a brief overview of the most advanced edge computing surveys published in the last …
A two-stage reinforcement learning-based approach for multi-entity task allocation
Task allocation is a key combinatorial optimization problem, crucial for modern applications
such as multi-robot cooperation and resource scheduling. Decision makers must allocate …
such as multi-robot cooperation and resource scheduling. Decision makers must allocate …
Generative AI based secure wireless sensing for ISAC networks
Integrated sensing and communications (ISAC) is expected to be a key technology for 6G,
and channel state information (CSI) based sensing is a key component of ISAC. However …
and channel state information (CSI) based sensing is a key component of ISAC. However …
Failure-aware resource provisioning for hybrid computation offloading in cloud-assisted edge computing using gravity reference approach
MI Khaleel - Swarm and Evolutionary Computation, 2024 - Elsevier
This paper tackles the challenges of computation offloading in the cloud–edge paradigm.
Although many solutions exist for enhancing the server's computational and communication …
Although many solutions exist for enhancing the server's computational and communication …