Introduction to Wireless Sensor Networks Presented by Sushanth Sivaram Vallath

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

Wireless Sensors Telos 4/04 Robust Low Power 250kbps Easy to use Tiny sensing devices capable of wireless communication Small microcontroller 8 kB code 512 B data Simple, low-power radio 10 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”

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

Platforms Berkeley Motes Tiny OS nesC Ns-2 TOSSIM

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

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

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

Routing Protocols LEACH Directed Diffusion PEGASIS TEEN APTEEN Etc…

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

Management Issues Conversion of data to Information Data access control

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

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

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

Query scenario Sink Select temp from

Efficiency achieved through In-network aggregation

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

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

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

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

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

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

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: 544-550 [15] Chiranjeeb Buragohain, Divyakant Agrawal, and Subhash Suri, Power Aware Routing for Sensor Databases.

Thank You