When choosing the technology options to develop a wireless sensor network (WSN), it is vital that their performance levels can be assessed for the type of application intended. This book describes the different technology options - MAC protocols, routing protocols, localisation and data fusion techniques - and provides the means to numerically measure their performance, whether by simulation, mathematical models or experimental test beds. Case studies, based on the authors' direct experience of implementing wireless sensor networks, describe the design methodology and the type of measurements used, together with samples of the performance measurements attained.The book will enable you to answer vital questions such as:* How long will my network remain alive given the amount of sensing required of it?* For how long should I set the sleeping state of my motes?* How many sensors should I distribute to meet the expected requirements of the application?* What type of throughput should I expect as a function of the number of nodes deployed and the radio interface chosen (whether it be Bluetooth or Zigbee)?* How is the Packet Error Rate of my Zigbee motes affected by the selection of adjacent frequency sub bands in the ISM 2.4GHz band?* How is the localisation precision dependant on the number of nodes deployed in a corridor?Communications and signal processing engineers, researchers and graduate students working in wireless sensor networks will find this book an invaluable practical guide to this important technology."This book gives a proper balance between theory and application; it is a book for those R&D engineers that want to appreciate both why, how and in which domains Wireless Sensor Networks can be best applied." - Fabio Bellifemine, Telecom Italia"This book is a thorough and accessible exposition on wireless sensor networks with a good balance between theory and practice; it is valuable for both students and practicing engineers, and is an essential addition for engineering libraries." - Professor Moe Win, Associate Professor at the Laboratory for Information and Decision Systems (LIDS), Massachusetts Institute of Technology *Only book to examine wireless sensor network technologies and assess their performance capabilities against possible applications*Enables the engineer to choose the technology that will give the best performance for the intended application*Case studies, based on the authors' direct experience of implementing wireless sensor networks, describe the design methodology and the type of measurements used, together with samples of the performance measurements attained.
Cited By
- Wang T, Conti A and Win M (2019). Network Navigation With Scheduling, IEEE/ACM Transactions on Networking, 27:4, (1319-1329), Online publication date: 1-Aug-2019.
- Kaynia M, Buratti C and Verdone R (2019). On the performance of wireless ad hoc networks using bandwidth partitioning, Wireless Networks, 25:7, (4215-4229), Online publication date: 1-Oct-2019.
- Das S and Tripathi S (2018). Intelligent energy-aware efficient routing for MANET, Wireless Networks, 24:4, (1139-1159), Online publication date: 1-May-2018.
- Bernad J, Bobed C and Mena E Estimating local coverage areas for location dependent queries Proceedings of the 33rd Annual ACM Symposium on Applied Computing, (940-947)
- Mazuelas S, Shen Y and Win M (2018). Spatiotemporal Information Coupling in Network Navigation, IEEE Transactions on Information Theory, 64:12, (7759-7779), Online publication date: 1-Dec-2018.
- Primeau N, Falcon R, Abielmona R and Petriu E (2018). A Review of Computational Intelligence Techniques in Wireless Sensor and Actuator Networks, IEEE Communications Surveys & Tutorials, 20:4, (2822-2854), Online publication date: 1-Oct-2018.
- Calisti A, Dardari D, Pasolini G and Kieffer M Exploiting Node Memory for Finite-time Average Consensus over WSNs 2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), (1-7)
- Mahmood M, Welch I and Kasi M Multilateration-based Event Identification in a Wireless Sensor Network Proceedings of the Fourth International Conference on Engineering & MIS 2018, (1-5)
- Bernad J, Bobed C and Mena E Viewer of Synthetic Scenarios to Evaluate Estimators of Local Coverage Areas Based on Detected Objects Proceedings of the 14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, (547-548)
- Bernad J, Bobed C and Mena E Estimation of Local Coverage Areas Based on Detected Objects Proceedings of the 14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, (527-528)
- Zabini F, Pasolini G and Conti A On random sampling with nodes attraction: The case of Gauss-Poisson process 2017 IEEE International Symposium on Information Theory (ISIT), (2278-2282)
- Rosas F, Souza R, Pellenz M, Oberli C, Brante G, Verhelst M and Pollin S (2016). Optimizing the Code Rate of Energy-Constrained Wireless Communications With HARQ, IEEE Transactions on Wireless Communications, 15:1, (191-205), Online publication date: 1-Jan-2016.
- Zabini F and Conti A (2016). Inhomogeneous Poisson Sampling of Finite-Energy Signals With Uncertainties in
${\mathbb{R}}^{d}$ - (2015). A preferential attachment model for primate social networks, Computer Networks: The International Journal of Computer and Telecommunications Networking, 76:C, (207-226), Online publication date: 15-Jan-2015.
- Wenhan Dai , Yuan Shen and Win M (2015). Distributed Power Allocation for Cooperative Wireless Network Localization, IEEE Journal on Selected Areas in Communications, 33:1, (28-40), Online publication date: 1-Jan-2015.
- Midha S, Sharma A and Sikka G (2014). A survey on wireless sensor network clustering protocols optimized via game theory, ACM SIGBED Review, 11:3, (8-18), Online publication date: 25-Nov-2014.
- Wang Y, Leus G and Deliç H (2014). Time-of-arrival estimation by UWB radios with low sampling rate and clock drift calibration, Signal Processing, 94, (465-475), Online publication date: 1-Jan-2014.
- Campos L, Oliveira R, Melo J and Neto A Overhead-Controlled routing in WSNs with reinforcement learning Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning, (622-629)
- Lo C, Qian K and Zhang Y Teaching operating systems with simple low-cost portable energy efficient devices Proceedings of the 49th Annual Southeast Regional Conference, (25-30)
- Chen J A dependable middleware for the development of applications for wireless sensor and actor networks Proceedings of the 13th international conference on Ubiquitous computing, (535-538)
- Kone C, David M and Lepage F Multi-channel clustering algorithm for improving performance of large-scale wireless multi-sink sensor networks Proceedings of the 6th International Wireless Communications and Mobile Computing Conference, (691-695)
- Niewiadomska-Szynkiewicz E and Sikora A A software tool for federated simulation of wireless sensor networks and mobile ad hoc networks Proceedings of the 10th international conference on Applied Parallel and Scientific Computing - Volume Part I, (303-313)
- Fabbri F, Gezer C and Verdone R The impact of realistic footprint shapes on the connectivity of wireless sensor networks Proceedings of the Fourth International ICST Conference on Performance Evaluation Methodologies and Tools, (1-7)
- Zabini F and Conti A Ginibre sampling and signal reconstruction 2016 IEEE International Symposium on Information Theory (ISIT), (865-869)
Recommendations
Testbed Environment for Wireless Sensor and Actuator Networks
ICSNC '10: Proceedings of the 2010 Fifth International Conference on Systems and Networks CommunicationsThe Wireless Sensor and Actuator Networks (WSAN’s), defines collaborative operations between the sensors and the actuators, enabling distributed sensing of a physical phenomenon. In this paper, an integrated testbed consisted of wireless sensor network, ...
K-Hop Coverage and Connectivity Aware Clustering in Different Sensor Deployment Models for Wireless Sensor and Actuator Networks
In wireless sensor and actuator networks, WSAN, actuators often act as cluster headers. Since the transmission range of actuator is much larger than that of sensor, both of the coverage of actuator and the connectivity of sensor-actuator require to be ...
Relay Node Placement in Wireless Sensor Networks
A wireless sensor network consists of many low-cost, low-power sensor nodes, which can perform sensing, simple computation, and transmission of sensed information. Long distance transmission by sensor nodes is not energy efficient since energy ...