This book discusses the challenges in the convergence of technologies as the Internet of Things (Io T) evolves. These include sensing, computing, information processing, networking, and controlling intelligent technologies. The contributors first provide a survey of various assessment and evaluation approaches available for successful convergence. They then go on to cover several operational ideas to apply. The contributors then discuss the challenges involved bridging gaps in computation and the communication process, hidden networks, intelligent decision making, human-to-machine perception and large-scale Io T environments. The contributors aim to provide the reader an overview of trends in Io T in terms of performability and traffic modeling and efforts that can be spent in assessing the graceful degradation in Io T paradigms.
- Provides a survey of Io T assessment and evaluation approaches;
- Covers new and innovative operational ideas that applyto the Io T industry and the industries it affects;
- Includes chapters from researchers and industry leaders in Io T from around the world.
Cuprins
Chapter1: Performability Analysis Methods for Clustered WSNs as Enabling Technology for Io T.- Chapter2: Practical Performability Assessment for Zigbee-based Sensors in the Io T Era.- Chapter3: Evaluation of Simulation Approaches and Need for MDE in Energy Effeciency, Performance and Availability Assessment of Io T.- Chapter4: False Data Injection Attacks in Internet of Things.- Chapter5: Energy Efficient Clustering for Wireless Sensor Devices in Internet of Things.- Chapter6: Toward optimum topology protocol in health monitoring.- Chapter7: Internet of Things (Io T) Considerations, Requirements, and Architectures for Disaster Management System.- Chapter8: Internet of Things and Statistical Analysis.- Chapter9: Internet of Vehicle (Io V) Applications in Expediting the Implementation of Smart Highway of Autonomous Vehicle: A Survey.- Chapter10: Virtual Coordinate Systems and Coordinate-based Operations for Io T.- Chapter11: Small Data in Io T: An MCS Perspective.