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A Distributed Deep Reinforcement Learning Technique for Application
  Placement in Edge and Fog Computing Environments

A Distributed Deep Reinforcement Learning Technique for Application Placement in Edge and Fog Computing Environments

24 October 2021
M. Goudarzi
M. Palaniswami
Rajkumar Buyya
    OffRL
ArXivPDFHTML

Papers citing "A Distributed Deep Reinforcement Learning Technique for Application Placement in Edge and Fog Computing Environments"

13 / 13 papers shown
Title
Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey
Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey
J. H. Liu
Yao Du
Kun Yang
Yan Wang
Xiping Hu
Z. Wang
Y. Liu
Peng Sun
Azzedine Boukerche
Victor C.M. Leung
43
0
0
03 May 2025
DRLQ: A Deep Reinforcement Learning-based Task Placement for Quantum
  Cloud Computing
DRLQ: A Deep Reinforcement Learning-based Task Placement for Quantum Cloud Computing
H. T. Nguyen
Muhammad Usman
Rajkumar Buyya
19
0
0
03 Jul 2024
TPTO: A Transformer-PPO based Task Offloading Solution for Edge
  Computing Environments
TPTO: A Transformer-PPO based Task Offloading Solution for Edge Computing Environments
N. Gholipour
M. D. Assunção
Pranav Agarwal
Julien Gascon-Samson
Rajkumar Buyya
11
1
0
18 Dec 2023
μ-DDRL: A QoS-Aware Distributed Deep Reinforcement Learning
  Technique for Service Offloading in Fog computing Environments
μ-DDRL: A QoS-Aware Distributed Deep Reinforcement Learning Technique for Service Offloading in Fog computing Environments
M. Goudarzi
M. A. Rodriguez
Majid Sarvi
Rajkumar Buyya
OffRL
15
0
0
13 Oct 2023
Deep Reinforcement Learning-based Scheduling for Optimizing System Load
  and Response Time in Edge and Fog Computing Environments
Deep Reinforcement Learning-based Scheduling for Optimizing System Load and Response Time in Edge and Fog Computing Environments
Zhiyu Wang
M. Goudarzi
Mingming Gong
Rajkumar Buyya
18
57
0
14 Sep 2023
FLight: A Lightweight Federated Learning Framework in Edge and Fog
  Computing
FLight: A Lightweight Federated Learning Framework in Edge and Fog Computing
Wu-Yang Zhu
M. Goudarzi
Rajkumar Buyya
FedML
27
7
0
05 Aug 2023
GA-DRL: Graph Neural Network-Augmented Deep Reinforcement Learning for
  DAG Task Scheduling over Dynamic Vehicular Clouds
GA-DRL: Graph Neural Network-Augmented Deep Reinforcement Learning for DAG Task Scheduling over Dynamic Vehicular Clouds
Zhang Liu
Lianfeng Huang
Zhibin Gao
Manman Luo
Seyyedali Hosseinalipour
H. Dai
GNN
11
14
0
03 Jul 2023
GiPH: Generalizable Placement Learning for Adaptive Heterogeneous
  Computing
GiPH: Generalizable Placement Learning for Adaptive Heterogeneous Computing
Yi Hu
Chao Zhang
Edward Andert
Harshul Singh
Aviral Shrivastava
James Laudon
Yan-Quan Zhou
Bob Iannucci
Carlee Joe-Wong
9
1
0
23 May 2023
A Decade of Research in Fog computing: Relevance, Challenges, and Future
  Directions
A Decade of Research in Fog computing: Relevance, Challenges, and Future Directions
Thang M. Pham
36
52
0
03 May 2023
TinyML: Tools, Applications, Challenges, and Future Research Directions
TinyML: Tools, Applications, Challenges, and Future Research Directions
Rakhee Kallimani
K. Pai
Prasoon Raghuwanshi
S. Iyer
O. López
36
40
0
23 Mar 2023
Scheduling IoT Applications in Edge and Fog Computing Environments: A
  Taxonomy and Future Directions
Scheduling IoT Applications in Edge and Fog Computing Environments: A Taxonomy and Future Directions
M. Goudarzi
M. Palaniswami
Rajkumar Buyya
13
69
0
26 Apr 2022
Container Orchestration in Edge and Fog Computing Environments for
  Real-Time IoT Applications
Container Orchestration in Edge and Fog Computing Environments for Real-Time IoT Applications
Zhiyuan Wang
M. Goudarzi
Jagannath Aryal
Rajkumar Buyya
22
21
0
10 Mar 2022
Integration of FogBus2 Framework with Container Orchestration Tools in
  Cloud and Edge Computing Environments
Integration of FogBus2 Framework with Container Orchestration Tools in Cloud and Edge Computing Environments
Zhiyu Wang
Rajkumar Buyya
19
1
0
04 Dec 2021
1