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Dynamic Scheduling for Stochastic Edge-Cloud Computing Environments
  using A3C learning and Residual Recurrent Neural Networks

Dynamic Scheduling for Stochastic Edge-Cloud Computing Environments using A3C learning and Residual Recurrent Neural Networks

1 September 2020
Shreshth Tuli
Shashikant Ilager
K. Ramamohanarao
Rajkumar Buyya
ArXivPDFHTML

Papers citing "Dynamic Scheduling for Stochastic Edge-Cloud Computing Environments using A3C learning and Residual Recurrent Neural Networks"

12 / 12 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
Jing Liu
Yao Du
Kun Yang
Yan Wang
Xiping Hu
Zehua Wang
Yang Liu
Peng Sun
Azzedine Boukerche
Victor C.M. Leung
43
0
0
03 May 2025
Task Placement and Resource Allocation for Edge Machine Learning: A
  GNN-based Multi-Agent Reinforcement Learning Paradigm
Task Placement and Resource Allocation for Edge Machine Learning: A GNN-based Multi-Agent Reinforcement Learning Paradigm
Yihong Li
Xiaoxi Zhang
Tian Zeng
Jingpu Duan
Chuanxi Wu
Di Wu
Xu Chen
21
15
0
01 Feb 2023
AI-based Fog and Edge Computing: A Systematic Review, Taxonomy and
  Future Directions
AI-based Fog and Edge Computing: A Systematic Review, Taxonomy and Future Directions
Sundas Iftikhar
S. Gill
Chenghao Song
Minxian Xu
M. Aslanpour
...
Félix Cuadrado
Blesson Varghese
Omer F. Rana
Schahram Dustdar
Steve Uhlig
39
132
0
09 Dec 2022
AI Augmented Edge and Fog Computing: Trends and Challenges
AI Augmented Edge and Fog Computing: Trends and Challenges
Shreshth Tuli
Fatemeh Mirhakimi
Samodha Pallewatta
Syed Zawad
G. Casale
B. Javadi
Feng Yan
Rajkumar Buyya
N. Jennings
21
56
0
01 Aug 2022
A Combination of Host Overloading Detection and Virtual Machine
  Selection in Cloud Server Consolidation based on Learning Method
A Combination of Host Overloading Detection and Virtual Machine Selection in Cloud Server Consolidation based on Learning Method
Huixi Li
Yinhao Xiao
Yongluo Shen
13
1
0
28 Jun 2022
SplitPlace: AI Augmented Splitting and Placement of Large-Scale Neural
  Networks in Mobile Edge Environments
SplitPlace: AI Augmented Splitting and Placement of Large-Scale Neural Networks in Mobile Edge Environments
Shreshth Tuli
G. Casale
N. Jennings
16
31
0
21 May 2022
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
15
69
0
26 Apr 2022
GOSH: Task Scheduling Using Deep Surrogate Models in Fog Computing
  Environments
GOSH: Task Scheduling Using Deep Surrogate Models in Fog Computing Environments
Shreshth Tuli
G. Casale
N. Jennings
26
21
0
16 Dec 2021
MCDS: AI Augmented Workflow Scheduling in Mobile Edge Cloud Computing
  Systems
MCDS: AI Augmented Workflow Scheduling in Mobile Edge Cloud Computing Systems
Shreshth Tuli
G. Casale
N. Jennings
26
36
0
14 Dec 2021
PreGAN: Preemptive Migration Prediction Network for Proactive
  Fault-Tolerant Edge Computing
PreGAN: Preemptive Migration Prediction Network for Proactive Fault-Tolerant Edge Computing
Shreshth Tuli
G. Casale
N. Jennings
35
38
0
04 Dec 2021
START: Straggler Prediction and Mitigation for Cloud Computing
  Environments using Encoder LSTM Networks
START: Straggler Prediction and Mitigation for Cloud Computing Environments using Encoder LSTM Networks
Shreshth Tuli
S. Gill
Peter Garraghan
Rajkumar Buyya
G. Casale
N. Jennings
AI4TS
14
25
0
19 Nov 2021
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
M. Goudarzi
M. Palaniswami
Rajkumar Buyya
OffRL
35
85
0
24 Oct 2021
1