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edge-computing-q-learning

Q learning and DQN

edge-intelligence

随着移动云计算和边缘计算的快速发展，以及人工智能的广泛应用，产生了边缘智能(Edge Intelligence)的概念。深度神经网络(例如CNN)已被广泛应用于移动智能应用程序中，但是移动设备有限的存储和计算资源无法满足深度神经网络计算的需求。神经网络压缩与加速技术可以加速神经网络的计算，例如剪枝、量化、卷积核分解等。但是这些技术在实际应用非常复杂，并且可能导致模型精度的下降。在移动云计算或边缘计算中，任务卸载技术可以突破移动终端的资源限制，减轻移动设备的计算负载并提高任务处理效率。通过任务卸载技术优化深度神经网络成为边缘智能研究中的新方向。Neurosurgeon: Collaborative Intelligence Between the Cloud and Mobile Edge这篇

fanqiang

翻墙-科学上网

game-theoretic-deep-reinforcement-learning

Code of Paper "Joint Task Offloading and Resource Optimization in NOMA-based Vehicular Edge Computing: A Game-Theoretic DRL Approach", JSA 2022.

github520

:kissing_heart: 让你“爱”上 GitHub，解决访问时图裂、加载慢的问题。（无需安装）

google-mirrors

Google谷歌、Wikipedia维基百科、谷歌学术镜像2023最新 新增各种镜像站

graduationproject

基于深度强化学习的MEC计算卸载与资源分配

graph-network-properties

Network Properties in Spark GraphFrames In this project, you will implement various network properties using pySpark and GraphFrames. You may need to look into the documentation for GraphFrames and networkx to complete this project. In addition to implementing these network metrics, you will be required to answer some questions when applying these

hdeft-experiments

resource allocation based on DAG

icc_2022_cbq

ICC 2022 submit paper code

interview_reference

2021年最新总结，阿里，腾讯，百度，美团，头条等技术面试题目，以及答案，专家出题人分析汇总。

job_shop_scheduling_problem_with_reinforcement_learning

This is the implemention of JSSP with RL. The framework used for RL is actor critic and the dataset comes from Tianchi competition.

lantern

Lantern官方版本下载 蓝灯 翻墙 代理 科学上网 外网 加速器 梯子 路由 lantern proxy vpn censorship-circumvention censorship gfw accelerator

mec_dag_ppo

Simulate one server for one user, use PPO.

mecoptimaloffloading

Optimization of Offloading Scheme Algorithm for Large Number of Tasks in Mobile-Edge Computing

mergingandscheduling

This is the code for the paper titleed task merge and scheduling for deep learning applications in mobile edge computing

mmap

大创-基于边缘计算的道路行程时间预测 用于展示成果的地图应用

multi-agent-mec_offloading-use_drl

使用Drl来解决多智能体卸载问题

offloading_to_vehicles_2

peerj-computer-science

python_platerecogntion

python opencv 车牌识别 PlateRecogntion

rdws

A real-time workflow scheduling system in a cloud computing environment with a deep reinforcement learning approach

reinforcement-learning

Minimal and Clean Reinforcement Learning Examples

reinforcement-learning-algorithms

This repository contains most of pytorch implementation based classic deep reinforcement learning algorithms, including - DQN, DDQN, Dueling Network, DDPG, SAC, A2C, PPO, TRPO. (More algorithms are still in progress)

reinforcement-learning-for-resource-allocation-tasks-in-the-cloud

reinforcement-learning-with-tensorflow-2.0

Tensorflow 2.0 Reinforcement Learning

resource-allocation-and-route-plannig-for-uavs

resources-allocation-in-the-edge-computing-environment-using-reinforcement-learning

Simulated the scenario between edge servers and users with a clear graphic interface. Also, implemented the continuous control with Deep Deterministic Policy Gradient (DDPG) to determine the resources allocation (offload targets, computational resources, migration bandwidth) in the edge servers

rl_ardrone

Autonomous Navigation of UAV using Reinforcement Learning algorithms.

rltaskoffloading