Directed Diffusion for Wireless Sensor Networking

1
Directed Diffusion for Wireless Sensor Networking

• C. Intanagonwiwat, R. Govindan, D. Estrin,
• John Heidemann, and Fabio Silva
• ACM/IEEE 2003
• ??? ???

2
Sensor Network Structure

• Sensor field ?? ???? ??? ??
• Sink ????? ???? ??
• Event ??? ????? ??

3
Contents

• Introduction
• Directed Diffusion
• Simplified schematic for Directed Diffusion
• Data Naming
• Interest Gradient
• Interest Propagation
• Data Propagation
• Reinforcement
• Simulations
• Conclusion

4
Introduction (1/2)

• Wireless sensor networks
• Sensing devices with communication capability
• Event monitoring
• Enemy detection, aircraft interiors, large
  industrial plants
• Data-centric communication
• Data is named by attribute-value
• Different form IP-style communication
• End-to-end delivery service

A sensor field
Sources
Event
Sink Node
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Introduction (2/2)

• Data-centric communication (cont.)
• Human operators query (task) is diffused
• Sensors begin collecting information about query
• Information returns along the reverse path
• Intermediate nodes aggregate the data
• Combing reports from sensors
• Challenges
• Scalability
• Energy efficiency
• Robustness / Fault tolerance in outdoor areas
• Efficient routing

6
Simplified schematic for Directed Diffusion

• (a) Sink? Interest ???? ??? ??
• (b) ??? ??? ?? ????
• (c) ??? ??
• (d) ??? ???? ??

7
Data Naming

• Content based naming
• Task are named Attribute value pair
• Selecting naming scheme important
• No globally unique ID for nodes only locally
  unique

Reply Data type four-legged animal
interval 1s rect -100,100,200,200
timestamp 012040 expiresAt 013040
Request Interest type four-legged animal
interval 20 ms duration 10 seconds
rect -100,100,200,200
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Interest Gradient

• Interest describes a task needed to be done by
  the sensor network
• Interests are injected into the network at sink.
• Sink broadcasts the interest.
• Interval specifies an event data rate.
• Initially, requested interval much larger than
  needed.
• Node maintains an interest cache.
• Interest entry also maintains gradients.
• Specifies a data rate and a direction (neighbor)
• Data flows from the source to the sink along the
  gradient

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Interest Propagation

• Flooding
• Constrained or Directional flooding based on
  location.
• Directional Propagation based on previously
  cached data.

Gradient
Source
Interest
Sink
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Data Propagation

• Reinforcement to single path delivery.
• Multipath delivery with probabilistic forwarding.
• Multipath delivery with selective quality along
  different paths.

Gradient
Source
Data
Sink
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Reinforcement

• Reinforce one of the neighbor after receiving
  initial data.
• Neighbor(s) from whom new events received.
• Neighbor whos consistently performing better
  than others.
• Neighbor from whom most events received.

Gradient
Source
Data
Reinforcement
Sink
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Negative Reinforcement(1/2)

• Explicitly degrade the path by re-sending
  interest with lower data rate.
• Time out

Gradient
Source
Data
Reinforcement
Sink
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Negative Reinforcement(2/2)

• Using negative reinforcement
• Path Truncation
• Loop removal
• For resource saving
• B negative reinforces D, D negative reinforces E,
  

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Performance Evaluation (1/7)

• Simulator ns-2
• Network Size 50-250 Nodes
• Transmission Range 40m
• Constant Density 1.95x10-3 nodes/m2 (9.8 nodes
  in radius)
• MAC Modified Contention-based MAC
• Transceiver Energy Model mimics a sensor radio
• 660 mW in transmission, 395 mW in reception, and
  35 mW in idle
• Comparison with
• Flooding
• Omniscient multicast

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Performance Evaluation (2/7)

• Average dissipated energy

0.018
0.016
Flooding
0.014
0.012
0.01
0.008
(Joules/Node/Received Event)
Omniscient Multicast
Average Dissipated Energy
0.006
Diffusion
0.004
Due to the data-aggregation Nodes suppress
duplicate location estimates
0.002
0
0
50
100
150
200
250
300
Network Size
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Performance Evaluation (3/7)

• Average delay

0.35
0.3
Flooding
0.25
0.2
Average Delay (secs)
0.15
0.1
Omniscient Multicast
Diffusion
0.05
0
Uncongested sensor network Reinforcement rules
find the low delay path
0
50
100
150
200
250
300
Network Size
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Performance Evaluation (4/7)

• Impact of dynamics (Distinct event delivery
  ratio)

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Performance Evaluation (5/7)

• Impact of negative reinforcement

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Performance Evaluation (6/7)

• Impact of duplicate suppression

Negative reinforcement
Suppress identical data sent
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Performance Evaluation (7/7)

• High idle radio power

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Conclusion

• Application-level data dissemination has the
  potential to improve energy efficiency
  significantly
• Data-centric dissemination
• Reinforcement based adaptation of paths
• Duplicate suppression and aggregation
• MAC for sensor networks needs to be designed
  carefully.