Code for paper "Computation Offloading Optimization for UAV-assisted Mobile Edge Computing: A Deep Deterministic Policy Gradient Approach"
Algorithm implementation for my Edge Computing-related papers.
Optimization of Offloading Scheme Algorithm for Large Number of Tasks in Mobile-Edge Computing
Source code for the paper "Joint Class-Balanced Client Selection and Bandwidth Allocation for Cost-Efficient Federated Learning in Mobile Edge Computing Networks".
This project is the implementation of the research paper titled "Dynamic Request Scheduling Optimization in Mobile Edge Computing for IoT Applications"
Open5GS 5GC & UERANSIM UE / RAN Sample Configuration
AdvantEDGE, Mobile Edge Emulation Platform
free5GC 5GC & UERANSIM UE / RAN Sample Configuration
Source code for the paper "Group-based Federated Learning with Cost-efficient Sampling Mechanism in Mobile Edge Computing Networks".
Joint Task Offloading and Radio Resource Management in Stochastic MEC Systems, IEEE Transactions on Communications, 2024
Simulation code for "A max-min task offloading algorithm for mobile edge computing using non-orthogonal multiple access," by V. Kumar, M. F. Hanif, M. Juntti and L. -N. Tran, published in IEEE Transactions on Vehicular Technology, vol. 72, no. 9, pp. 12332-12337, Sept. 2023, doi: 10.1109/TVT.2023.3263791.
This is a repository for my Diploma Thesis on Wireless Communications at Aristotle University of Thessaloniki
Open5GS EPC & OpenAirInterface UE / RAN Sample Configuration
QECO: A QoE-Oriented Computation Offloading Algorithm based on Deep Reinforcement Learning for Mobile Edge Computing
Multi-Agent Deep Reinforcement Learning for Collaborative Computation Offloading in Mobile Edge-Computing
本项目是我发表于期刊 Expert Systems with Applications 的论文《Energy-efficient mechanism of task offloading and resource allocation for hierarchical MEC in UAV-assisted mmWave IABN》的官方代码实现。我们提出了一种基于深度学习的方法,旨在最小化复杂的无人机辅助边缘计算网络中的系统能耗,同时保证服务质量。
Multi-UAV Assisted Mobile Edge Computing: A hybrid optimization approach of combining multi-agent RL techniques with collaborative and adaptive caching policies for supporting mobile edge computing through UAVs.
Add a description, image, and links to the mobile-edge-computing topic page so that developers can more easily learn about it.
To associate your repository with the mobile-edge-computing topic, visit your repo's landing page and select "manage topics."