A novel offloading strategy for multi-user optimization in blockchain-enabled Mobile Edge Computing networks for improved Internet of Things performance

AM Rahmani, J Tanveer, FS Gharehchopogh… - Computers and …, 2024 - Elsevier
As blockchain technology merges with Mobile Edge Computing (MEC) and the Internet of
Things (IoT), we encounter increasing challenges such as high energy consumption and …

The role of mobile edge computing in advancing federated learning algorithms and techniques: A systematic review of applications, challenges, and future directions

AM Rahmani, S Alsubai, A Alanazi, A Alqahtani… - Computers and …, 2024 - Elsevier
Abstract Mobile Edge Computing (MEC) and Federated Learning (FL) have recently
attracted considerable interest for their potential applications across diverse domains. MEC …

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 …

A joint optimization of resource allocation management and multi-task offloading in high-mobility vehicular multi-access edge computing networks

H Min, AM Rahmani, P Ghaderkourehpaz… - Ad Hoc Networks, 2025 - Elsevier
Vehicular communications have advanced data exchange and real-time services in
intelligent transportation systems by exploiting advanced communication between vehicles …

URLLC-aware and energy-efficient data offloading strategy in high-mobility vehicular mobile edge computing environments

H Min, J Tanveer, AM Rahmani, A Alqahtani… - Vehicular …, 2024 - Elsevier
The integration of Internet of Things (IoT) technologies into the vehicular industry has
initiated a new era of connected and autonomous vehicles, revolutionizing transportation …

Reinforcement Learning Based Edge-End Collaboration for Multi-Task Scheduling in 6G Enabled Intelligent Autonomous Transport Systems

P Li, Z **ao, H Gao, X Wang… - IEEE Transactions on …, 2025 - ieeexplore.ieee.org
As communication and computing technologies advance, vehicular edge computing
emerges as a promising paradigm for delivering a wide array of intelligent services in 6G …

An advanced deep reinforcement learning algorithm for three-layer D2D-edge-cloud computing architecture for efficient task offloading in the Internet of Things

K Moghaddasi, S Rajabi, FS Gharehchopogh… - … Informatics and Systems, 2024 - Elsevier
Abstract The Internet of Things (IoTs) has transformed the digital landscape by
interconnecting billions of devices worldwide, paving the way for smart cities, homes, and …

A novel energy-efficient and cost-effective task offloading approach for UAV-enabled MEC with LEO enhancement in Internet of Remote Things networks

AM Rahmani, A Haider, S Alsubai, A Alqahtani… - … Modelling Practice and …, 2024 - Elsevier
Abstract The Internet of Remote Things (IoRT) involves networks of devices deployed in
extensive and often remote areas, collecting data for transmission and processing. In such …

Enhancing healthcare IoT systems for diabetic patient monitoring: Integration of Harris Hawks and grasshopper optimization algorithms

M Hosseinzadeh, Z Arabi, S Ali, H Min, MH Malik - Plos one, 2024 - journals.plos.org
The integration of the Internet of Things (IoT) in healthcare, especially for people with
diabetes, allows for constant health monitoring. This means that doctors can watch over …

Leveraging 5G Technology to Investigate Energy Consumption and CPU Load at the Edge in Vehicular Networks

SE Merzougui, X Limani, A Gavrielides… - World Electric Vehicle …, 2024 - mdpi.com
The convergence of vehicular communications, 5th generation mobile network (5G)
technology, and edge computing marks a paradigm shift in intelligent transportation …