Task-Offloading Optimization Using a Genetic Algorithm in Hybrid Fog Computing for the Internet of Drones

Sensors, Год журнала: 2025, Номер 25(5), С. 1383 - 1383

Опубликована: Фев. 24, 2025

Research and development on task offloading over the Internet of Drones (IoD) has expanded rapidly in last few years. Task a fog IoD environment is very challenging due to high dynamics topology, which cause intermittent connections, as well stringent requirements offloading, such reduced delay. To overcome these challenges, this paper, we propose task-offloading optimization strategy using heuristic genetic algorithm (GA) with hybrid computing technology for Drones, named GA Hybrid-Fog. The proposed solution employs from edge Unmanned Aerial Vehicles (UAVs) both base stations (FBSs) UAVs (FUAVs) order optimize delays (transmission delays) guarantee higher storage processing capacity. Experimental results show that Hybrid-Fog achieves greater improvements compared other technologies (GA BS-Fog, UAV-Fog, UAV-Edge).

Язык: Английский

Task Offloading Optimization Using PSO in Fog Computing for the Internet of Drones

Drones, Год журнала: 2024, Номер 9(1), С. 23 - 23

Опубликована: Дек. 30, 2024

Recently, task offloading in the Internet of Drones (IoD) is considered one most important challenges because high transmission delay due to mobility and limited capacity drones. This particularity makes it difficult apply conventional technologies, such as cloud computing edge computing, IoD environments. To address these limits, ensure a low delay, this paper we propose PSO BS-Fog, optimization that combines particle swarm (PSO) heuristic with fog technology for IoD. The proposed solution applies from unmanned aerial vehicles (UAVs) base stations (FBSs) order optimize (transmission delay) guarantee higher storage processing capacity. performance BS-Fog was evaluated through simulations conducted MATLAB environment compared against UAV-Fog UAV-Edge technologies. Experimental results demonstrate reduces by up 88% 97% UAV-Edge.

Язык: Английский

A Distributed Training Framework for Cross-Domain Heterogeneous Clusters

Опубликована: Дек. 27, 2024

Язык: Английский