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Deep reinforcement learning for application scheduling in resource-constrained, multi-tenant serverless computing environments

  • Published:2023-06 Issue: Volume:143 Page:277-292
  • ISSN:0167-739X
  • Container-title:Future Generation Computer Systems
  • language:en
  • Short-container-title:Future Generation Computer Systems

Author:

Mampage AnupamaORCID,Karunasekera ShanikaORCID,Buyya Rajkumar

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Reference49 articles.

1. Home — OpenFaaS - Serverless functions made simple;OpenFaaS,2022

2. Home - knative;Authors,2022

3. Fission;Project,2022

4. Peeking behind the curtains of serverless platforms;Wang,2018

5. ENSURE: Efficient scheduling and autonomous resource management in serverless environments;Suresh,2020

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1. Deep Convolutional Neural Network with a Fuzzy (DCNN-F) technique for energy and time optimized scheduling of cloud computing;Cluster Computing;2024-07-04

2. Reinforcement Learning Based Memory Configuration for Linear Dynamic Function Chains;2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD);2024-05-08

3. Dynamic Scheduling Algorithms for Serverless Computing Solutions in the Cloud;2024 International Conference on E-mobility, Power Control and Smart Systems (ICEMPS);2024-04-18

4. A scalable modified deep reinforcement learning algorithm for serverless IoT microservice composition infrastructure in fog layer;Future Generation Computer Systems;2024-04

5. Edge-computing-assisted intelligent processing of AI-generated image content;Journal of Real-Time Image Processing;2024-02-25
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