Cloud Computing Enabled Big-Data Analytics in Wireless Ad-hoc Networks

Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Preface
Editors
Contributors
About This Book
Chapter 1 Cloud-Based Underwater Ad-hoc Communication: Advances, Challenges, and Future Scopes
	1.1 Introduction
	1.2 Communication with the Sensors
	1.3 Connecting the Sensors with the Cloud
		1.3.1 Architecture of the Underwater Sensor Network with Cloud Computing
	1.4 Various Outcomes of Cloud Integration
		1.4.1 A Trust Model Based on Cloud Theory in Underwater Acoustic Sensor Networks
		1.4.2 An Energy-Balanced Trust Cloud Migration Scheme for Underwater Acoustic Sensor Networks
		1.4.3 Bidirectional Prediction-Based Underwater Data Collection Protocol for End-Edge-Cloud Orchestrated System
		1.4.4 An Underwater IoT System, Creating a Smart Ocean
		1.4.5 CUWSN: An Energy-Efficient Routing Protocol for the Cloud-Based Underwater Ad-hoc Communication Network
		1.4.6 SoftWater: Software-Defined Networking
	1.5 Various Challenges in a Cloud-Based Underwater Communication Network
	1.6 Future Scope
	References
Chapter 2 A Hybrid Cryptography Technique with Blockchain for Data Integrity and Confidentiality in Cloud Computing
	2.1 Introduction
		2.1.1 Security Issues in Cloud Computing
	2.2 Related Work
	2.3 Problem Definition
	2.4 Objectives
	2.5 Proposed Methodology
		2.5.1 Registration Phase
		2.5.2 Data Confidentiality Using Hybrid Algorithm
		2.5.3 Secure Data Integrity and the Transaction
			2.5.3.1 The Setup Phase
			2.5.3.2 Check Proof Phase
	2.6 Performance Analysis
		2.6.1 The Simulation Results
		2.6.2 Signature Verification
	2.7 Conclusion
	References
Chapter 3 Fog Computing Environment in Flying Ad-hoc Networks: Concept, Framework, Challenges, and Applications
	3.1 Introduction
		3.1.1 Motivation
		3.1.2 Organization
	3.2 Fog Computing
	3.3 UAV-Based Fog Computing
	3.4 Framework and Architecture of UAV-Based Fog
	3.5 Challenges for UAV-Based Fog
	3.6 Applications and Scope of UAV-Based Fogs
	3.7 Techniques for Implementation and Experiments
	3.8 Conclusion
	References
Chapter 4 Wi-Fi Computing Network Empowers Wi-Fi Electrical Power Network
	4.1 Objectives of the Chapter
	4.2 Increased Flexibility a Must for the Future Power Utility Constructs
	4.3 Energy Importance for Data Centres and Network Stations and Costs of Energy
	4.4 Computing Has Full Synergy with Energy
	4.5 Wireless Power Transmission
	4.6 Leadership in Innovation
	4.7 Long and Short of Wi-Fi
	4.8 Conclusions
	Acknowledgements
	Bibliography
Chapter 5 Big Data Analytics for Vehicular Edge Networks
	5.1 Introduction
		5.1.1 Impacts of Intelligent Computing Technologies in VANET
		5.1.2 Wireless Communication Technologies
	5.2 Big Data Analytics
		5.2.1 Data Mining Techniques in the VANET
		5.2.2 Machine Learning for VANET
	5.3 Edge-Enabled Data Gathering and Aggregation
		5.3.1 Data Gathering
		5.3.2 Data Aggregation
	5.4 Edge-Enabled Service Content Prefetching and Storing
	5.5 Edge-Enabled Computing
	5.6 Result and Discussion
	5.7 Data Analysis
	5.8 Conclusion
	References
Chapter 6 Impact of Various Parameters on Gauss Markov Mobility Model to Support QoS in MANET
	6.1 Introduction
	6.2 GM Mobility Model
	6.3 Simulation Results
		6.3.1 Simulation Parameters
		6.3.2 Experimental Results
	6.4 Results and Discussion
	6.5 Conclusion and Future Work
	References
Chapter 7 Heterogeneous Ad-hoc Network Management: An Overview
	7.1 Introduction
		7.1.1 Wired and Wireless Communication Design Approach
		7.1.2 Enabling and Networking Technologies
		7.1.3 Taxonomy of HANET
	7.2 Mobile Ad-hoc Network (MANET)
		7.2.1 Overview of MANET
		7.2.2 Simulation Results
	7.3 Wireless Sensor Network (WSN)
		7.3.1 Overview of WSN
		7.3.2 Routing Protocol of WSN
	7.4 Vehicular Ad-hoc Network (VANET)
		7.4.1 Characteristics
		7.4.2 Applications
	7.5 Wireless Mesh Network (WMN)
	7.6 Common Characteristics of HANET
	7.7 Common Issues of HANET
	7.8 Intelligent Management Requirement in HANET
	References
Chapter 8 Deployment of the Biometrics-as-a-Service (BaaS) Design for the Internet of Biometric Things (IoBT) on the AWS Cloud
	8.1 Introduction
	8.2 Strengthening Security of Transactions through Blockchain DB
	8.3 Biometric Software as a Service (BAAS)
	8.4 BAAS and Cloud Biometrics
	8.5 Existing Work
		8.5.1 Biometric Trait Capture and Preprocessing
		8.5.2 Extraction of FVs
		8.5.3 Matching
		8.5.4 Decision
		8.5.5 Classification
	8.6 Modification of Existing System
	8.7 BAAS Deployment on Amazon AWS Cloud
	8.8 IoBT Backend
		8.8.1 Step 1: Login to Your AWS Console and Create Instance
		8.8.2 Step 2: Login, Configure and Run
		8.8.3 Step 3: Build and Run Models on AWS
		8.8.4 Step 4: Close Your EC2 Instance
	8.9 Proposed System and Initial Deployment Results
	8.10 Conclusion
	Acknowledgments
	References
Chapter 9 A Comprehensive Survey of Geographical Routing in Multi-hop Wireless Networks
	9.1 Introduction: An Overview
		9.1.1 Challenges Related to Mobility in Multi-Hop Wireless Networks
		9.1.2 Simulator Support for Mobility Models in Multi-hop Wireless Networks
	9.2 Various Routing Protocols Applied for MWNs, MANETs, VANET, WSN
		9.2.1 Geographical Routing Protocols for MWNs
			9.2.1.1 Classification of Geographic Routing
			9.2.1.2 Greedy-Based Routing
			9.2.1.3 Face Routing
			9.2.1.4 GFG Routing
			9.2.1.5 Opportunistic Routing
			9.2.1.6 Void Handling in Geographical Routing
		9.2.2 Geographical Routing in MANET
			9.2.2.1 Geographical Routing in Aeronautical Ad hoc Network (AANET)
		9.2.3 Geographical Routing in WSN
			9.2.3.1 Geographical Routing in Underwater Wireless Sensor Network (UWSN)
			9.2.3.2 Geographical Routing in VANET
			9.2.3.3 Geographical Routing in DTN
	9.3 Future Work and Research Challenges
	9.4 Conclusion
	References
Chapter 10 Energy-Aware Secure Routing in Sensor Network
	10.1 Introduction
	10.2 Literature Survey
	10.3 Assumptions Considered in the Proposal
	10.4 Proposed Work
	10.5 Simulation
		10.5.1 Energy Consumption
	10.6 Conclusion
	References
Chapter 11 Deploying Trust-Based E-Healthcare System Using Blockchain-IoT in Wireless Networks
	11.1 Introduction
		11.1.1 A Brief State of the Art in Terms of Study Hypotheses
	11.2 Related Work
		11.2.1 International Status
		11.2.2 National Status
	11.3 Blockchain Technology in E-Healthcare System
		11.3.1 Different Aspects of Blockchain
		11.3.2 Features of E-Healthcare System Using Blockchain
		11.3.3 Working Principle of Blockchain
		11.3.4 Importance of the Proposed Paper in the Context of the Current Status
	11.4 Technical Details of IoT-Blockchain for E-Healthcare System
		11.4.1 Model Implementation
	11.5 Conclusion
	References
Chapter 12 Low Cost Robust Service Overloading Fusion Model for Cloud Environments
	12.1 Introduction
	12.2 Cloud Computing Environment Security Issues
	12.3 Objectives and Significance
		12.3.1 Objective
	12.4 Fusion Model
		12.4.1 Cloud Overloading
		12.4.2 Service Overloading
	12.5 The Proposed Model
	12.6 Overloading Authentication System
	12.7 Implementation and Results
		12.7.1 The Simulation Environment
		12.7.2 Simulation Results and Analysis
	12.8 Conclusion
	References
Chapter 13 Load Balancing Based on Estimated Finish Time of Services
	13.1 Introduction
		13.1.1 Sorts of Cloud Computing
	13.2 Load Balancing
	13.3 Related Work
	13.4 Proposed Load Balancing Algorithm
	13.5 Proposed Methodology
	13.6 Imitation and Outcome Analysis
		13.6.1 CloudSim
		13.6.2 Netbeans (Software)
	13.7 Experimental Results
		13.7.1 Waiting Time of Proposed Algorithm
		13.7.2 Turnaround Time of Proposed Algorithm
		13.7.3 Processing Cost of Proposed Algorithm
	13.8 Conclusion and Future Work
	References
Chapter 14 Blockchain-Enabled Smart Contract Optimization for Healthcare Monitoring Systems
	14.1 Introduction
		14.1.1 Blockchain
		14.1.2 Ethereum
		14.1.3 Smart Contract
			14.1.3.1 Smart Legal Contracts
			14.1.3.2 Decentralized Autonomous Organization (DAO)
			14.1.3.3 Application Logic Contracts (ALCs)
		14.1.4 Gas Optimization Techniques
	14.2 Literature Survey
	14.3 Methodology
		14.3.1 Designing of Healthcare System Smart Contract on Ethereum Blockchain
		14.3.2 Writing Healthcare System Smart Contract Using Sublime Text 3 and Remix Ethereum IDE
		14.3.3 Optimization Techniques Applied on Smart Contract to Reduce the Gas Cost
	14.4 Results
	14.5 Conclusion
	References
Chapter 15 Interference Mitigation Using Cognitive Femtocell from 5G Perspective
	15.1 Introduction
	15.2 Motivation
	15.3 Objective
	15.4 Literature Review
	15.5 System Model
		15.5.1 Functions of CFC
		15.5.2 Biasing and SINR
		15.5.3 Minimizing Interference
		15.5.4 The Resource Allocation Process
	15.6 Results and Discussion
	15.7 Conclusion
	References
Index