
Randomly Deployed Wireless Sensor Networks
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Wireless sensor networks have a range of applications, including military uses and in environmental monitoring. When an area of interest is inaccessible by conventional means, such a network can be deployed in ways resulting in a random distribution of the sensors. Randomly Deployed Wireless Sensor Networks offers a probabilistic method to model and analyze these networks. The book considers the network design, coverage, target detection, localization and tracking of sensors in randomly deployed wireless networks, and proposes a stochastic model. It quantifies the relationship between parameters of the network and its performance, and puts forward a communication protocol. The title provides analyses and formulas, giving engineering insight into randomly deployed wireless sensor networks. Five chapters consider the analysis of coverage performance; working modes and scheduling mechanisms; the relationship between sensor behavior and network performance properties; probabilistic forwarding routing protocols; localization methods for multiple targets and target number estimation; and experiments on target localization and tracking with a Mica sensor system.
Key Features
- Details a probabilistic method to model and analyze randomly deployed wireless sensor networks
- Gives working modes and scheduling mechanisms for sensor nodes, allowing high-probability of target detection
- Considers the relationship between sensor behaviour and network performance and lifetime
- Offers probabilistic forwarding routing protocols for randomly deployed wireless sensor networks
- Describes a method for localizing multiple targets and estimating their number
Readership
Researchers, academics, practicing engineers, and advanced students working on wireless sensor networks
Table of Contents
- Chapter 1: introduction
1.1 Summary of wireless sensor networks
1.2 Research topics in wireless sensor networks
1.3 Applications of wireless sensor networks
1.4 Outline of the book
Chapter 2: Coverage in wireless sensor networks
2.1 Coverage in WSNs: Elements
2.2 Coverage in WSNs: Research status
2.3 Coverage in WSNs: Challenges
Chapter 3: Coverage performance in randomly distributed WSNs
3.1 Point Coverage in homogeneous networks
3.2 Point Coverage in heterogeneous networks
3.3 Simulation experiments
3.4 Conclusion
Chapter 4: Percentage Coverage deployment
4.1 Percentage Coverage deployment with localization
4.2 Percentage Coverage deployment without localization
4.3 Conclusion
Chapter 5: Dynamic target detection
5.1 State switching scheme for sensors
5.2 Analysis of detection probability
5.3 Optimization
5.4 Application example
5.5 Conclusion
Chapter 6: Stochastic model of wireless sensor networks
6.1 Model description
6.2 Stochastic scheduling
6.3 Stochastic scheduling with node failure rate
6.4 Performance improvement
6.5 Conclusion
Chapter 7: Probabilistic Forwarding (ProFor) routing protocol
7.1 Routing protocol
7.2 Model of ProFor
7.3 Network simulator ns2 and Simulation of ProFor
7.4 Simulation results and analysis
7.5 Conclusion
Chapter 8: Extension for ProFor routing protocol
8.1 ProFor with packet loss rate
8.2 Packet merge
8.3 Nodes energy cost for ProFor
8.4 Node’s state switch and multiple bases
8.5 Conclusion
Chapter 9: Energy-based Multiple targets localization
9.1 Target localization and tracking: Research status
9.2 Multiple targets localization with target number
9.3 Estimation of target number
9.4 Conclusion
Chapter 10: Experiment study: target localization
10.1 MICA system
10.2 common methods for target localization
10.3 Experiment results
10.4 Conclusion
Product details
- No. of pages: 134
- Language: English
- Copyright: © Elsevier 2020
- Published: June 18, 2020
- Imprint: Elsevier
- eBook ISBN: 9780128227718
- Paperback ISBN: 9780128196243
About the Author
Xi Chen
Xi Chen is Associate Professor in the Department of Automation at Tsinghua University in China. She received her PhD from the Chinese University of Hong Kong. Her research focuses on stochastic control and optimisation, the Markov decision process, wireless sensor networks, and evolutionary computing. Currently, she plays a leading role in the Department of Automation, working on wireless sensor networks. She has published over 50 papers, and four books.
Affiliations and Expertise
Associate Professor, Department of Automation, Tsinghua University, Tsinghua, China
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