1. Introduction to Wireless Sensor Networks
Presented by
Sushanth Sivaram Vallath

2. The most profound technologies are those that disappear
The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it.
- The late Mark Weiser, Father of Ubiquitous Computing and Chief Technologist of Xerox PARC

3. Wireless Sensors
Telos 4/04
Robust
Low Power
250kbps
Easy to use
Tiny sensing devices capable of wireless communication
Small microcontroller kB code B data
Simple, low-power radio kbps ASK
EEPROM (32 KB)
Simple sensors
WeC 99
“Smart Rock”
Rene 11/00
Designed for experimentation
sensor boards
power boards
Mica 1/02
NEST open exp. Platform 128 kB code, 4 kB data 40kbps OOK/ASK radio 512 kB Flash
Dot 9/01
Demonstrate scale
Mica2 12/02
38.4kbps radio FSK
Before we jump in to the technical material, I would like to give you one more bit of context.
Spec 6/03
“Mote on a chip”

4. What are sensor networks
spatially distributed sensors to monitor conditions at different locations, such as temperature, sound, vibration, pressure, motion or pollutants.

5. Platforms
Berkeley Motes
Tiny OS
nesC
Ns-2
TOSSIM

6. Applications of WSN Temperature Humidity Vehicular movement Pressure
Noise levels
Mechanical stress levels on attached objects
Speed, direction
Etc…

7. Factors Influencing Sensor Network Design
Fault tolerance
Scalability
Operating environment
Sensor network topology
Transmission media
Power consumption

8. Sensors Representation
Communication Graph
Sensors are nodes
Link between the sensors are the edges

9. Routing Protocols
LEACH
Directed Diffusion
PEGASIS
TEEN
APTEEN
Etc…

10. Sensor Issues Energy Constraint High Communication cost
& Lot of other issues

11. Management Issues Conversion of data to Information
Data access control

12. SQL Underlying routing protocol transparent to user
Some routing protocols are considered to be aggregation protocols (implicit aggregation)

13. Sensor Database SQL type interface SELECT avg(temperature), room,
FROM sensors
WHERE building = “Nedderman Hall”
ORDER BY temperature
GROUP BY room
SAMPLING PERIOD 10 min

14. SQL type interfaces Cougar TinyDB Approximations Query Propagation
Data Centric Storage
Aging Data

15. Query scenario
Sink
Select temp from

16. Efficiency achieved through
In-network aggregation

17. Different types of queries
Fully aggregated queries
Un-aggregated queries
Partially aggregated queries

18. Fully aggregated queries
Theorem: Finding maximum lifetime routing tree for fully aggregated queries with reception costs is NP-complete.
Similar to Minimum Degree Spanning Tree(MDST) which is known to be NP-complete

19. Un-aggregated queries
Theorem: Finding maximum lifetime routing tree for unaggregated queries is NP-complete.
Reduced from decision problem for SET-COVER.

20. Partially aggregated queries
Can be reduced to unaggregated queries
Approximation algorithms used to solve the unaggregated routing tree problem can be adapted.

21. Active areas in WSN Routing Topology control
Data management, aggregation and query
MAC protocols
Target tracking, resource discovery
Monitoring and maintenance
Sensor validation
Power issues
Coverage and Connectivity

22. Companies in Research Crossbow Intel IBM Microsoft PARC Fujitsu
Lot more…

23. References
[1] Cedric Florens and Robert McEliece, “Packet Distribution Algorithms for Sensor Networks”, IEEE INFOCOM 2003.
[2] Samuel Madden, Robert Szewczyk, Michael J. Franklin and David Culler, “Supporting Aggregate Queries Over Ad-Hoc Wireless Sensor Networks”,
[3] Sartaj Sahni and Xiaochun Xu, Algorithms for Wireless Sensor Networks.
[4] Jamal N. Al-Karaki Ahmed E. Kamal, Routing Techniques in Wireless Sensor Networks: A Survey.
[5] Bhaskar Krishnamachari, D Estrin, Stephen Wicker, Modeling Data-Centric Routing in Wireless Sensor Networks.
[6] S.S Iyengar, Richard R. Brooks, “Distributed Sensor Networks”, Chapman & Hall/CRC.
[7] Wendi Rabiner Heinzelman, Anantha Chandrakasan, and Hari Balakrishnan, “Energy-efficient communication protocol for wireless microsensors networks,” in 33rd Annual Hawaii International conference on System Sciences.
[8] David Braginsky and Deborah Estrin, “Rumor routing algorithm for sensor networks,” in First ACM International Workshop on Wireless Sensor Networks and Application.
[9] Y.Xu, J. Heidemann, and D. Estrin, “Geography-informed energy conservation for ad hoc routing,” in Proceedings of the Seventh Annual ACM/IEEE International Conference on Mobile Computing and Networking, 2001.
[10] B. Chen, K. Jamieson, H. Balakrishnan, and R. Morris, “SPAN: An energy-efficient coordination algorithm for topology maintenance in ad-hoc wireless networks,” ACM Wireless Networks Journal, September 2002.
[11] Feng Zhao and Leonidas Guibas, “Wireless Sensor Networks, an Information Processing Approach”.
[12] Yong Yao, J. E. Gehrke. The Cougar Approach to In-Network Query Processing in Sensor Networks. Sigmod Record, Volume 31, Number 3. September 2002.
[13] Yong Yao, J. E. Gehrke. Query Processing in Sensor Networks. In Proceedings of the First Biennial Conference on Innovative Data Systems Research (CIDR 2003). Asilomar, California, January 2003.
[14] Xiuli Ma, Dongqing Yang, Shiwei Tang, Qiong Luo, Dehui Zhang, and Shuangfeng Li. Online Mining in Sensor Networks. NPC 2004:
[15] Chiranjeeb Buragohain, Divyakant Agrawal, and Subhash Suri, Power Aware Routing for Sensor Databases.

24. Thank You