On Using Probabilistic Forwarding to Improve HEC-based Data Forwarding in Opportunistic Networks

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On Using Probabilistic Forwarding to Improve
HEC-based Data Forwarding in Opportunistic
Networks

• Ling-Jyh Chen1, Cheng-Long Tseng2 and Cheng-Fu
  Chou2
• 1Academia Sinica
• 2National Taiwan University

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Motivation

• There are numerous opportunistic networking
  applications.
• wireless sensor network, underwater sensor
  network, pocket switched network, people network,
  and transportation network
• Traditional data forwarding algorithms are not
  suitable for opportunistic networks.
• Scheduled optimal routing method
• Mobile relay approaches (Message ferry)

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Related work

• Replication-based approaches
• The messages are replicated. Several identical
  copies are transmitted over the networks to
  mitigate the effects of a single path failure.
• For example
• Epidemic Routing,
• Controlled Flooding,
• mobility pattern-based scheme (Prophet)

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Related work

• Coding-based approaches
• Transforming a message into another format prior
  to transmission.
• For example
• Erasure coding (EC), Aggressive Erasure Coding
  (A-EC), Hybrid Erasure Coding (H-EC)
• Network Coding

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Our Contribution

• We propose a message scheduling algorithm,
  Probabilistic Forwarding, to improve H-EC scheme.
• Using a set of simulations, we show the proposed
  approach can provide better data delivery
  performance.

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Overview of H-EC

• Erasure Coding
• Providing better fault-tolerance by adding
  redundancy without the overhead of strict
  replication.
• Reed-Solomon,
• Low-Density Parity-Check (LDPC) based coding
  (Gallager, Tornado, and IRA codes)

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Erasure Coding
(r,n)(2,4)
A
B
C
D
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Overview of H-EC
EC erasure coding
(r2, n4)
A-EC erasure coding aggressive forwarding
(r2, n4)
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Overview of H-EC

• H-EC Hybrid of EC and A-EC
• First copy is sent using EC
• Second copy is sent using A-EC during the
  residual contact duration after sending the first
  EC block

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The Purposed Method HEC-PF

• Probabilistic forwarding
• The HEC-PF scheme dost NOT enter the aggressive
  forwarding phase unless a newly encountered node
  has a higher likelihood of successfully
  forwarding the message to the destination node
  that the current nodes.
• Delivery Probability

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Delivery Probability

• Based on the observed contact history
• Take the contact frequency and contact volume
  into consideration.
• The proportion of time that the two nodes are in
  contact in the last T time units.

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Delivery Probability
One-hop delivery probability
K number of nodes in the network Xi the i-th
node tXiXjthe aggregated contact volume
between the node pair Xi and Xj in the last T
time units
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Delivery Probability
Two-hop delivery probability
Three-hop delivery probability
k-hop delivery probability
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Probabilistic Forwarding
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Evaluation

• DTNSIM A Java-based DTN simulator
• Performance metric
• Delay performance
• Transmission overhead
• Evaluating Scenarios

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Evaluation I two-hop scenario
Evaluate the delay performance of the HEC-PF
scheme for message delivery. Maximum message
delivery distance (hops) H2, The transitive
property of message delivery (hops) K2
UCSD Scenario
Power-Low Scenario
ZebraNet Scenario
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Evaluation II Variable k Scenarios
We evaluate the performance with various k values
(k 2,3,4,5)
ZebraNet Scenario
UCSD Scenario
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Evaluation II Variable k Scenarios
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Evaluation IIIVariable H Scenarios
We evaluate the performance with various maximum
forwarding distance settings (H 2,3,4,5)
UCSD Scenario
ZibraNet Scenario
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Evaluation II Variable H Scenarios
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Conclusion

• We purposes a new scheme for data forwarding by
  incorporating the basic H-EC scheme with a new
  feature, Probabilistic Forwarding.
• Using simulations as well as both synthetic and
  realistic network traces, we show that the
  proposed has better performance in terms of
  delivery latency and completion ratio.
• We show that the completion ratio improves as the
  maximum forwarding distance or the considered hop
  distance of the delivery probability increases.

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Thank You!