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Design and Implementation of the Deep Reinforcement Energy Efficient Routing for the Fog-BAN-Cloud of Things using Smart Health care applications Cover

Design and Implementation of the Deep Reinforcement Energy Efficient Routing for the Fog-BAN-Cloud of Things using Smart Health care applications

Open Access
|Feb 2025

Figures & Tables

Figure 1:

Working Mechanism of the Proposed methodology
Working Mechanism of the Proposed methodology

Figure 2:

PPO Framework
PPO Framework

Figure 3:

Energy Efficient Routing mechanism
Energy Efficient Routing mechanism

Figure 3:

Performance metrics comparsion
Performance metrics comparsion

Figure 4:

body area network -data transmission
body area network -data transmission

Figure 4:

Energy Consumption Analysis
Energy Consumption Analysis

Parameters of Simulation Used in the Experiment

S.NoSimulation ParametersSpecifications
1No of Nodes deployed120
2No of Fog gateways07
3Initial Energy in each BAN Nodes0.0016 Joules
4Distance variation from each BAN nodes5-10metres
5Transceivers EquippedWIFI
6Uplink Bandwidth200 Mbps
7Downlink Bandwidth100 Mbps
8RAM in Fog gateways2.5GB
9No of Attributes recorded08

Evaluation Metrices

SL.NOPerformance MetricsMathematical Expression
01AccuracyTP+TNTP+TN+FP+FN
02Sensitivity or recallTPTP+FN×100
03SpecificityTNTN+FP
04PrecisionTNTP+FP
05F1-Score2.Precison*RecallPrecision+Recall
Language: English
Page range: 42 - 54
Submitted on: Aug 17, 2024
Accepted on: Sep 25, 2024
Published on: Feb 24, 2025
Published by: Future Sciences For Digital Publishing
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2025 Pradeep Kumar S, S. Venkatramulu, Siva Surya Narayana Chintapalli, published by Future Sciences For Digital Publishing
This work is licensed under the Creative Commons Attribution 4.0 License.