Bellypoly / On_simulating_energy_consumption_of_federated_learning_systems
A simulation of energy consumption of a federated learning system based on the non-orthogonal multiple access (NOMA) transmission protocols, proposed by Mo et. al. Energy consumption is computed during training along with energy consumed by communications between local machines and the server.
☆25Updated 4 years ago
Alternatives and similar repositories for On_simulating_energy_consumption_of_federated_learning_systems:
Users that are interested in On_simulating_energy_consumption_of_federated_learning_systems are comparing it to the libraries listed below
- Federated Learning for Energy-balanced Client Selection in Mobile Edge Computing☆35Updated 8 months ago
- ☆21Updated last year
- Federated Learning over Wireless Networks: Convergence Analysis and Resource Allocation☆31Updated 3 years ago
- FLASH-RL (Federated Learning Addressing System and Static Heterogeneity using Reinforcement Learning) is a novel and effective strategy f…☆36Updated 8 months ago
- ☆64Updated 3 years ago
- Federated Learning over Wireless Networks☆44Updated 3 years ago
- Exploring Deep Reinforcement Learning-Assisted Federated Learning for Online Resource Allocation in Privacy-Preserving EdgeIoT☆28Updated 9 months ago
- Compression-based decentralized stochastic gradient descent (DSGD) algorithms tailored for digital and analog wireless implementations☆12Updated 2 years ago
- Migration of Edge-based Distributed Federated Learning☆23Updated 2 years ago
- ☆12Updated last year
- ☆17Updated last year
- Code for the case study presented in "Making a Case for Federated Learning in the Internet of Vehicles and Intelligent Transportation Sys…☆24Updated 3 years ago
- Game Theory Based Distributed Resource Allocation in Communication Networks☆21Updated 4 years ago
- ☆26Updated last year
- Energy-Spectral Efficiency Optimization in Vehicular Communications: Joint Clustering and Pricing-based Robust Power Control Approach☆14Updated 4 years ago
- Simulation code of our paper in IEEE Transactions on Cognitive Communications and Networking: ''Energy-Efficient Blockchain-enabled User…☆43Updated 10 months ago
- Federated Reinforcement Learning project☆26Updated last year
- Apply Deep Reinforcement Learning aided by Federated Learning to Wireless Comunication☆111Updated 3 years ago
- qiongwu86 / Asynchronous-Federated-Learning-Based-Mobility-aware-Caching-in-Vehicular-Edge-Computing☆76Updated last year
- This is a repository for the implementation of the paper "Green, Quantized Federated Learning over Wireless Networks: An Energy-Efficient…☆11Updated last year
- ☆44Updated 3 years ago
- Code for paper "A Distributed ADMM Approach for Collaborative Regression Learning in Edge Computing"☆57Updated last year
- learn to allocate wireless resources with GNN in over-the-air FL system☆10Updated last year
- Adaptive Offloading of Federated Learning on IoT Devices☆70Updated 2 years ago
- part code of paper entitled "battery-constrained federated edge learning in uav-enabled iot for b5g/6g networks"☆21Updated 3 years ago
- A collection for Paper/code for Wireless Communication Optimization Problems with PyTorch based DL☆25Updated 4 years ago
- Source code for paper "Federated Edge Learning with Misaligned Over-The-Air Computation"☆25Updated last year
- This is the code for paper: Scalable Federated Multi-agent Architecture forNetworked Communication Scenarios☆18Updated 3 years ago
- This project is created for the simulations of the paper: [Wang2021] Wenbo Wang, Amir Leshem, Dusit Niyato and Zhu Han, "Decentralized L…☆30Updated 3 years ago
- Joint Task Offloading and Radio Resource Management in Stochastic MEC Systems, IEEE Transactions on Communications, 2024☆21Updated last year