Collaborative cloud and edge computing for latency minimization

J Ren, G Yu, Y He, GY Li - IEEE Transactions on Vehicular …, 2019 - ieeexplore.ieee.org
By performing data processing at the network edge, mobile edge computing can effectively
overcome the deficiencies of network congestion and long latency in cloud computing …

Collaborative cloud-edge-end task offloading in mobile-edge computing networks with limited communication capability

C Kai, H Zhou, Y Yi, W Huang - IEEE Transactions on Cognitive …, 2020 - ieeexplore.ieee.org
Mobile edge computing (MEC) is an emerging computing paradigm for enabling low-
latency, high-bandwidth and agile mobile services by deploying computing platform at the …

Joint multi-user computation offloading and data caching for hybrid mobile cloud/edge computing

X Yang, Z Fei, J Zheng, N Zhang… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
In this paper, we investigate a hybrid mobile cloud/edge computing system with coexistence
of centralized cloud and mobile edge computing, which enables computation offloading and …

Cooperative service caching and workload scheduling in mobile edge computing

X Ma, A Zhou, S Zhang, S Wang - IEEE INFOCOM 2020-IEEE …, 2020 - ieeexplore.ieee.org
Mobile edge computing is beneficial for reducing service response time and core network
traffic by pushing cloud functionalities to network edge. Equipped with storage and …

Joint offloading and resource allocation for computation and communication in mobile cloud with computing access point

MH Chen, B Liang, M Dong - IEEE INFOCOM 2017-IEEE …, 2017 - ieeexplore.ieee.org
We consider a general multi-user mobile cloud computing system with a computing access
point (CAP), where each mobile user has multiple independent tasks that may be processed …

Collaborate edge and cloud computing with distributed deep learning for smart city internet of things

H Wu, Z Zhang, C Guan, K Wolter… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
City Internet-of-Things (IoT) applications are becoming increasingly complicated and thus
require large amounts of computational resources and strict latency requirements. Mobile …

Joint task assignment, transmission, and computing resource allocation in multilayer mobile edge computing systems

P Wang, C Yao, Z Zheng, G Sun… - IEEE Internet of Things …, 2018 - ieeexplore.ieee.org
In this paper, we propose a multilayer data flow processing system, ie, EdgeFlow, to
integrally utilize the computing capacity throughout the whole network, ie, the cloud center …

Advanced deep learning-based computational offloading for multilevel vehicular edge-cloud computing networks

M Khayyat, IA Elgendy, A Muthanna… - IEEE …, 2020 - ieeexplore.ieee.org
The promise of low latency connectivity and efficient bandwidth utilization has driven the
recent shift from vehicular cloud computing (VCC) towards vehicular edge computing (VEC) …

Cooperative task offloading in three-tier mobile computing networks: An ADMM framework

Y Wang, X Tao, X Zhang, P Zhang… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The deployment of cloud and edge computing forms a three-tier mobile computing network,
where each task can be processed locally, by the edge nodes, or by the remote cloud …

Multi-agent deep reinforcement learning for task offloading in UAV-assisted mobile edge computing

N Zhao, Z Ye, Y Pei, YC Liang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Mobile edge computing can effectively reduce service latency and improve service quality
by offloading computation-intensive tasks to the edges of wireless networks. Due to the …