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Full Description
The Internet of Things (IoT) networks have revolutionized the world and have innumerable real-time applications on automation. A few examples include driverless cars, remote monitoring of the elderly, remote order of tea or coffee of your choice from a vending machine, and home/industrial automation amongst others.
Fundamentals of Internet of Things build the foundations of IoT networks by leveraging the relevant concepts from signal processing, communications, net-works, and machine learning. The book covers two fundamental components of IoT networks, namely, the Internet and Things. In particular, the book focuses on networking concepts, protocols, clustering, data fusion, localization, energy harvesting, control optimization, data analytics, fog computing, privacy, and security including elliptic curve cryptography and blockchain technology. Most of the existing books are theoretical and without many mathematical details and examples. In addition, some essential topics of the IoT networks are also missing in the existing books.
Features:
• The book covers cutting-edge research topics
• Provides mathematical understanding of the topics in addition to relevant theory and insights
• Includes illustrations with hand-solved numerical examples for visualization of the theory and testing of understanding
• Lucid and crisp explanation to lessen the study time of the reader
The book is a complete package of the fundamentals of IoT networks and is suitable for graduate-level students and researchers who want to dive into the world of IoT networks.
Contents
1. Things and Internet. 1.1 Introduction. 1.2 Things. 1.3 Internet. 1.4 Summary. 1.5 Exercises. 2. Standards and Protocols. 2.1 Introduction. 2.2 IEEE 802.11 Protocol. 2.3 IEEE 802.15.4 Protocol. 2.4 LoRaWAN Protocol. 2.5 6LowPAN Protocol. 2.6 Application Protocols. 2.7 Summary. 2.8 Exercises. 3. Clustering and Data Fusion. 3.1 Introduction. 3.2 Clustering Technique. 3.3 Energy Efficient Clustering. 3.4 Sensor Data Fusion. 3.5 Dempster-Shafer Theory for Data Fusion. 3.6 Decision Fusion. 3.7 Summary. 3.8 Exercises. 4. Smart Device Localization. 4.1 Introduction. 4.2 Taxonomy of Localization Algorithms. 4.3 Distance-based Localization Methods. 4.4 Distance-free Localization Methods. 4.5 Performance Metrics. 4.6 Summary. 4.7 Exercises. 5. Energy Harvesting and Control Optimization. 5.1 Introduction. 5.2 Energy Harvesting. 5.3 Model Predictive Control. 5.4 Summary. 5.5 Exercises. 6. Things Data Analytics. 6.1 Introduction. 6.2 Understanding the Buzz Words. 6.3 Supervised Learning. 6.4 Unsupervised Learning. 6.5 Bias and Variance Tradeoff. 6.6 Artificial Neural Networks. 6.7 Evaluation Method. 6.8 Summary. 6.9 Exercises. 7. Fog Computing. 7.1 Introduction. 7.2 Technologies for Fog Computing. 7.3 Mobility in Fog Framework. 7.4 Fog Orchestration. 7.5 Localization in Fog Computing Framework. 7.6 Task Offloading. 7.7 Summary. 7.8 Exercises. 8. Privacy and Security of Things Data. 8.1 Introduction. 8.2 Data Privacy. 8.3 Elliptic Curve Cryptography. 8.4 Blockchain. 8.5 Summary. 8.6 Exercises. 9. Applications of IoT. 9.1 Introduction. 9.2 Smart Healthcare. 9.3 Smart City. 9.4 Summary. 9.5 Exercises
