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Energy and latency reductions at the fog gateway using a machine learning classifier

Published:2021-09 Issue: Volume:31 Page:100582
ISSN:2210-5379
Container-title:Sustainable Computing: Informatics and Systems
language:en
Short-container-title:Sustainable Computing: Informatics and Systems

Author:

Suryadevara Nagender Kumar^ORCID

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,General Computer Science

Reference29 articles.

1. Internet of things (IOT): an overview and its applications;Dudhe,2017

2. https://www.cisco.com/c/dam/en_us/solutions/trends/iot/docs/computing-overview.pdf accessed on 19, Nov-2019.

3. http://www.contrib.andrew.cmu.edu/∼mndarwis/ML.html, accessed on 19,Nov,2019.

4. MLscale: a machine learning based application-agnostic autoscaler;Wajahat;Sustain. Comput. Inform. Syst.,2019

5. WEEC: web energy efficient computing: a machine learning approach;Uzair;Sustain. Comput. Inform. Syst.,2019

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1. A Novel Offloading Mechanism Leveraging Fuzzy Logic and Deep Reinforcement Learning to Improve IoT Application Performance in a Three-Layer Architecture Within the Fog-Cloud Environment;IEEE Access;2024

2. Latency, Energy and Carbon Aware Collaborative Resource Allocation with Consolidation and QoS Degradation Strategies in Edge Computing;2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS);2023-12-17

3. Decision tree-based prediction approach for improving stable energy management in smart grids;Journal of High Speed Networks;2023-11-14

4. An Energy-Efficient Routing Protocol with Reinforcement Learning in Software-Defined Wireless Sensor Networks;Sensors;2023-10-13

5. Energy management of smart homes over fog-based IoT architecture;Sustainable Computing: Informatics and Systems;2023-09

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