A deep reinforcement learning based hybrid algorithm for efficient resource scheduling in edge computing environment

F Xue, Q Hai, T Dong, Z Cui, Y Gong - Information Sciences, 2022 - Elsevier
Edge computing can greatly decrease the delay between users and cloud servers, which
can significantly improve system service performance. However, it remains challenging for …

Deep Neural Networks meet computation offloading in mobile edge networks: Applications, taxonomy, and open issues

E Mustafa, J Shuja, F Rehman, A Riaz, M Maray… - Journal of Network and …, 2024 - Elsevier
Abstract Mobile Edge Computing (MEC) is a modern paradigm that involves moving
computing and storage resources closer to the network edge, reducing latency, and …

[HTML][HTML] Hybrid workload enabled and secure healthcare monitoring sensing framework in distributed fog-cloud network

A Lakhan, Q Mastoi, MA Dootio, F Alqahtani… - Electronics, 2021 - mdpi.com
The Internet of Medical Things (IoMT) workflow applications have been rapidly growing in
practice. These internet-based applications can run on the distributed healthcare sensing …

Utility optimization for multi-user task offloading in mobile ad hoc cloud: A stochastic game approach

F Zhang, R Deng, X Zhou… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Offloading tasks to the mobile ad hoc cloud (MAHC) can improve the utility of mobile devices
in scenarios without infrastructure. However, when multiple resource demanders (RDs) …

Joint program partitioning and resource allocation for completion time minimization in multi-MEC systems

T Yi, G Zhang, K Wang, K Yang - IEEE Transactions on Network …, 2022 - ieeexplore.ieee.org
This paper considers a practical mobile edge computing (MEC) system, where edge server
does not pre-install the program required to perform user offloaded computing tasks. A …

Performance Analysis of Task Offloading in Mobile Edge Cloud Computing for Brain Tumor Classification Using Deep Learning

R Yamuna, R Rajalingam, MU Rani - Journal of Applied Engineering …, 2023 - yrpipku.com
The increasing prevalence of brain tumors necessitates accurate and efficient methods for
their identification and classification. While deep learning (DL) models have shown promise …

Componentized Task Scheduling in Cloud-Edge Cooperative Scenarios Based on GNN-enhanced DRL

J Li, F Zhou, W Li, M Zhao, X Yan… - NOMS 2023-2023 IEEE …, 2023 - ieeexplore.ieee.org
With the continuous functional enhancement of network services, a service usually presents
a directed acyclic graphic (DAG) structure. This paper models the DAG task scheduling …

[PDF][PDF] Hybrid Workload Enabled and Secure Healthcare Monitoring Sensing Framework in Distributed Fog-Cloud Network. Electronics 2021, 10, 1974

A Lakhan, Q Mastoi, MA Dootio, F Alqahtani… - 2021 - academia.edu
The Internet of Medical Things (IoMT) workflow applications have been rapidly growing in
practice. These internet-based applications can run on the distributed healthcare sensing …

Research on Price-Based Autonomous Group Robot Resource Allocation Strategy in Emergency Scenarios

S Yi, Z Xiao - 2023 - researchsquare.com
In unknown and dynamic emergency scenarios, achieving the collaboration of autonomous
group robots for search and rescue operations can be regarded as resource allocation …

[HTML][HTML] Intelligent Scheduling Method Supporting Stadium Sharing

L Fang - Discrete Dynamics in Nature and Society, 2021 - hindawi.com
At present, the fast-paced work and life make people under great pressure, and people's
enthusiasm for fitness is getting higher and higher, which is in contradiction with the …