Building Efficient Wireless Sensor Networks with Low-Level Naming

1. Building Efficient Wireless Sensor Networks with Low-Level Naming J. Heidemann, F. Silva, C. Intanagonwiwat R. Govindan, D. Estrin, D. Ganesan Presented by Ke Liu CS552, Fall 2002 Binghamton University

2. Wireless Sensor Network • Features • Related low bandwidth • Limited power supply • Communication is much more expensive than Computation • May mobile sensor nodes • Problems • Existing network model assumes high power and high bandwidth • Layered naming

3. New Approach • To build distributed systems around attribute-named data & in-network processing • Using attributes with external to the network topology and relevant to the application Example: • The geographic information • The type of sensor nodes (e.g. computation capability) • Low-level communication is based on these attributes

4. Architecture • Directed Diffusion • To disseminate information • Matching Rules • To determinate when to process data • Filter • To process data based on specific application (especially about data aggregation)

5. Directed Diffusion • Goal: • to establish efficient n-way communication between one or more sources and sinks • An example

6. Step 1

7. Step 2

8. Step 3

9. Directed Diffusion Features • Data-Centric • Hop-by-Hop Communication (not End-to-End) • No need for global unique address • Coordinated Sensing close to the sensed phenomena • It is a general approach

10. Attribute Tuples • Diffusion message and Application Interests are composed of Attribute-value-operation tuples • Attribute-value-operation Tuples • Unique Keys from the Central Authority • In some data format • Compare the diffusion message and interests • Binary comparison operation for every field of the tuples

11. Matching Rules • Only each field of the Diffusion message tuple equals to that of the interests == Matching • Easy implementation • Example: detection of an animal in a particular region specified by a rectangle • Application may use only a subset of these method: • Omitting geographic constraints • Using a single attribute

12. Filter • Mechanism for allowing application-specific code to run in the network and assist diffusion and processing • Typically used for in-network aggregation • In-network data aggregation • Energy efficiency • No layered naming binding • Network auto-organization • Not resolved yet

13. Conclusion • Avoid multiple levels of name binding • Enable in-network processing • May enable in-network data aggregation • Others

14. Most important references • W. Adjie-Winoto, E. Schwartz, H. Balakrishnan, and J. Lilley. The design and implementation of an intentional naming system. In Proceedings of the 17th Symposium on Operating SystemsPrinciples, pages 186–201, Kiawah Island, SC, USA, Dec. 1999. ACM • W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan. Energy-efficient communication protocols for wireless microsensor networks. In Proceedings of the Hawaii International Conference on Systems Sciences, Jan. 2000. • Y. Yu, D. Estrin, and R. Govindan. Geographical and energy-aware routing for wireless sensor networks: A recursive data dissemination protocol. Work in Progress, Mar. 2001.

15. Thank You ! Any Questions