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Building Efficient Wireless Sensor Networks with Low-Level Naming Presented by Ke Liu CS552, Fall 2002 Binghamton University J. Heidemann, F. Silva, C.

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Presentation on theme: "Building Efficient Wireless Sensor Networks with Low-Level Naming Presented by Ke Liu CS552, Fall 2002 Binghamton University J. Heidemann, F. Silva, C."— Presentation transcript:

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

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 Systems Principles, 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


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