Improved snake optimization-based task scheduling in cloud computing

VK Damera, G Vanitha, B Indira, G Sirisha, R Vatambeti - Computing, 2024 - Springer
The recent focus on cloud computing is due to its evolving platform and features like
multiplexing users on shared infrastructure and on-demand resource computation. Efficient …

[PDF][PDF] Blockchain-enabled infrastructural security solution for serverless consortium fog and edge computing

AA Khan, AA Laghari, AM Baqasah, R Alroobaea… - PeerJ Computer …, 2024 - peerj.com
The robust development of the blockchain distributed ledger, the Internet of Things (IoT), and
fog computing-enabled connected devices and nodes has changed our lifestyle nowadays …

Multi-agent deep reinforcement learning for computation offloading in cooperative edge network

P Wu, Y Guan - Journal of Intelligent Information Systems, 2024 - Springer
Abstract Mobile Edge Computing (MEC) has emerged as an effective paradigm for reducing
latency and enhancing computational efficiency. However, the rapid proliferation of edge …

Joint UAV Deployment and Task Offloading in Large-Scale UAV-Assisted MEC: A Multiobjective Evolutionary Algorithm

Q Qiu, L Li, Z **ao, Y Feng, Q Lin, Z Ming - Mathematics, 2024 - mdpi.com
With the development of digital economy technologies, mobile edge computing (MEC) has
emerged as a promising computing paradigm that provides mobile devices with closer edge …

Deep reinforcement learning method for task offloading in mobile edge computing networks based on parallel exploration with asynchronous training

J Chen, L **, R Yao, H Zhang - Mobile Networks and Applications, 2024 - Springer
In mobile edge computing (MEC), randomly offloading tasks to edge servers (ES) can cause
wireless devices (WD) to compete for limited bandwidth resources, leading to overall …

Blockchain-enabled trust management for secure content caching in mobile edge computing using deep reinforcement learning

S Bounaira, A Alioua, I Souici - Internet of Things, 2024 - Elsevier
Mobile edge computing (MEC) has introduced content edge caching to offload network
backhaul and improve user quality of experience by transferring frequently requested …

5G and edge: A reinforcement learning approach for Virtual Network Embedding with cost optimization and improved acceptance rate

CL Moreira, CA Kamienski, RAC Bianchi - Computer Networks, 2024 - Elsevier
Abstract 5G technologies are fueling a revolution across numerous industries, including
manufacturing, healthcare, and entertainment, by enabling the development and …

DELIGHT: a willingness-aware collaborative edge service offloading utilizing deep reinforcement learning

H Ye, B Cao, Z Zeng, Y Hou, X Xu, B Tang - Cluster Computing, 2025 - Springer
Under the impetus of mobile edge computing, mobile access networks and the Internet are
deeply integrated providing low-latency, high-reliability computing power for service …

[HTML][HTML] Fault-Tolerant Scheduling Mechanism for Dynamic Edge Computing Scenarios Based on Graph Reinforcement Learning

Y Zhang, G **a, C Yu, H Li, H Li - Sensors, 2024 - mdpi.com
With the proliferation of Internet of Things (IoT) devices and edge nodes, edge computing
has taken on much of the real-time data processing and low-latency response tasks which …

Deep reinforcement learning-based optimal deployment of IoT machine learning jobs in fog computing architecture

O Bushehrian, A Moazeni - Computing, 2025 - Springer
By increasing the number and variety of areas where IoT technology is being applied, the
challenges regarding the design and deployment of IoT applications and services have …