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AI-Enabled 6G Networks and Applications

Objektkategorie:
Elektronische Ressource
Person/Institution:
Gupta, Deepak
Ragab, Mahmoud
Mansour, Romany Fouad
Khamparia, Aditya
Khanna, Ashish
Verlag:
John Wiley & Sons, Incorporated
Veröffentlichungsort:
Newark
Entstehungszeit:
2023
Umfang, Illustration, Format:
1 online resource (179 pages)
Sprache:
Englisch
Bereitstellende Institution:
Forschungsbibliothek Gotha
GND Explorer
Abstract:
Cover -- Title Page -- Copyright Page -- Contents -- List of Contributors -- Preface -- About the Editors -- Chapter 1 Metaheuristic Moth Flame Optimization Based Energy Efficient Clustering Protocol for 6G Enabled Unmanned Aerial Vehicle Networks -- 1.1 Introduction -- 1.2 The Proposed Model -- 1.2.1 Network Model -- 1.2.2 Algorithmic Procedure of MFO Algorithm -- 1.2.3 Design of MMFO-EEC Technique -- 1.3 Experimental Validation -- 1.4 Conclusion -- References -- Chapter 2 A Novel Data Offloading with Deep Learning Enabled Cyberattack Detection Model for Edge Computing in 6G Networks -- 2.1 Introduction -- 2.2 The Proposed Model -- 2.2.1 RNN Based Traffic Flow Forecasting -- 2.2.2 ASCE Based Data Offloading -- 2.2.3 SAE Based Cyberattack Detection -- 2.2.4 CSO Based Parameter Optimization -- 2.3 Performance Validation -- 2.4 Conclusion -- References -- Chapter 3 Henry Gas Solubility Optimization with Deep Learning Enabled Traffic Flow Forecasting in 6G Enabled Vehicular Networks -- 3.1 Introduction -- 3.2 The Proposed Model -- 3.2.1 Z-Score Normalization -- 3.2.2 DBN Based Prediction Model -- 3.2.3 HSGO Based Hyperparameter Optimization Model -- 3.3 Experimental Validation -- 3.4 Conclusion -- References -- Chapter 4 Crow Search Algorithm Based Vector Quantization Approach for Image Compression in 6G Enabled Industrial Internet of Things Environment -- 4.1 Introduction -- 4.2 The Proposed Model -- 4.2.1 Overview of VQ -- 4.2.2 LBG Model -- 4.2.3 Process Involved in CSAVQ-ICIIoT Model -- 4.3 Results and Discussion -- 4.4 Conclusion -- References -- Chapter 5 Design of Artificial Intelligence Enabled Dingo Optimizer for Energy Management in 6G Communication Networks -- 5.1 Introduction -- 5.2 The Proposed Model -- 5.2.1 Process Involved in DOA -- 5.2.2 Steps Involved in Energy Management Scheme.
Objekttext:
Description based on publisher supplied metadata and other sources

Zugriff und Nutzungsmöglichkeiten

Universität Erfurt
Forschungsbibliothek Gotha
Schloss Friedenstein
Schlossplatz 1
99867 Gotha
+49 361 737-5540
bibliothek.gotha(at)uni-erfurt.de
Datensatz angelegt am:
2023-04-12
Zuletzt geändert am:
2022-12-09
In Portal übernommen am:
2023-04-12