Cloud Computing Enabled Big-Data Analytics in Wireless Ad-hoc Networks (Wireless Communications and Networking Technologies)

✍ Scribed by Sanjoy Das (editor), Ram Shringar Rao (editor), Indrani Das (editor), Vishal Jain (editor)

• Publisher: CRC Press
• Tongue: English
• Leaves: 291
• Category: Library

✦ Synopsis

This book discusses intelligent computing through the Internet of Things (IoT) and Big-Data in vehicular environments in a single volume. It covers important topics, such as topology-based routing protocols, heterogeneous wireless networks, security risks, software-defined vehicular ad-hoc networks, vehicular delay tolerant networks, and energy harvesting for WSNs using rectenna.

FEATURES

• Covers applications of IoT in Vehicular Ad-hoc Networks (VANETs)

• Discusses use of machine learning and other computing techniques for enhancing performance of networks

• Explains game theory-based vertical handoffs in heterogeneous wireless networks

• Examines monitoring and surveillance of vehicles through the vehicular sensor network

• Investigates theoretical approaches on software-defined VANET

The book is aimed at graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science, and engineering.

✦ Table of Contents

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