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Building Efficient Wireless Sensor Networks with Low-Level Naming

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To build distributed systems around attribute-named data & in-network processing ... Attribute Tuples ... Using a single attribute. Filter ... – PowerPoint PPT presentation

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Title: 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 Systems
    Principles, pages 186201, 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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