Deep Reinforcement Learning-based scheduling for optimizing system load and response time in edge and fog computing environments

Author:

Wang Zhiyu,Goudarzi Mohammad,Gong Mingming,Buyya Rajkumar

Funder

Australian Research Council

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Reference64 articles.

1. Industrial internet of things (iiot) applications of edge and fog computing: A review and future directions;Chalapathi,2021

2. Deadline-aware and energy-efficient IoT task scheduling in fog computing systems: A semi-greedy approach;Azizi;J. Netw. Comput. Appl.,2022

3. Towards the decentralised cloud: Survey on approaches and challenges for mobile, ad hoc, and edge computing;Ferrer;ACM Comput. Surv.,2019

4. An application placement technique for concurrent IoT applications in edge and fog computing environments;Goudarzi;IEEE Trans. Mob. Comput.,2020

5. An IoT-aware architecture for smart healthcare systems;Catarinucci;IEEE Internet Things J.,2015

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