Computational Framework for Node Placement and Bandwidth Optimization in Dynamic Fog Computing Environments
Author:
Affiliation:
1. University of Visvesvaraya College of Engineering (UVCE),Department of Computer Science and Engineering,Bengaluru,India,560001
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10038981/10039721/10039819.pdf?arnumber=10039819
Reference17 articles.
1. Learning-in-the-Fog (LiFo): Deep Learning Meets Fog Computing for the Minimum-Energy Distributed Early-Exit of Inference in Delay-Critical IoT Realms
2. A Resource Management Model for Distributed Multi-Task Applications in Fog Computing Networks
3. Foundations and Evolution of Modern Computing Paradigms: Cloud, IoT, Edge, and Fog
4. Contract-Based Computing Resource Management via Deep Reinforcement Learning in Vehicular Fog Computing
5. Dynamic Task Placement for Deadline-Aware IoT Applications in Federated Fog Networks
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1. Anomaly Detection-Based Resource Autoscaling Mechanism for Fog Computing;Lecture Notes in Networks and Systems;2024
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