using redundancy to cope with failures in a delay tolerant network
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Using Redundancy to Cope with Failures in a Delay Tolerant Network. Sushant Jain, Michael Demmer, Rabin Patra, Kevin Fall Source: www.cs.utexas.edu/~lili/ classes/F05/slides/dtn-yogita.ppt . Outline of Discussion . Introduction Erasure Coding Formal Problem Statement Path Failure Models

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using redundancy to cope with failures in a delay tolerant network

Using Redundancy to Cope with Failures in a Delay Tolerant Network

Sushant Jain, Michael Demmer, Rabin Patra, Kevin Fall

Source: www.cs.utexas.edu/~lili/ classes/F05/slides/dtn-yogita.ppt

outline of discussion
Outline of Discussion
  • Introduction
  • Erasure Coding
  • Formal Problem Statement
  • Path Failure Models
  • Evaluation
  • Related Work
  • Conclusion
  • Future Development
introduction
Introduction
  • Routing in Delay Tolerant Network (DTN) in presence of path failures is difficult
  • Retransmissions cannot be used for reliable delivery
    • Timely feedback may not be possible
  • How to achieve reliability in DTN?
    • Replication, Erasure coding
erasure coding
Erasure Coding
  • N block message is encoded into large (>N) number of code blocks.
  • Message can be decoded when fraction 1/r or more blocks are received. Replication factor = r
  • Allocation of code blocks over different links not simple.
bernoulli path failure are identical and independent
Bernoulli Path Failure, are identical and independent
  • Family of allocation strategies is used

for kth strategy

  • Probability of success of kth strategy
slide9
Bernoulli Path Failure, are different

Formulation of Mixed Integer Program (MIP)

Objective Function:

partial path failures
Partial Path Failures

Objective: Maximize Sharpe Ratio

evaluation
Evaluation
  • Three scenarios used for evaluation:
    • DTN routing over data MULEs
      • Path independent, data loss Bernoulli
    • DTN routing over set of city buses
      • Paths dependent, data loss Bernoulli
    • DTN routing large sensor network
      • Partial path failures
data mule scenario
Data MULE Scenario
  • Simulation Setup:

1km x 1km planar area, source and destination at opposite corners.

Message size 10KB, Contact bandwidth 100Kbps, Storage capacity of MULE 1MB

Velocity of MULE 10m/s.

  • Probability of success of ith path is
  • Di is the delay in distribution by ith MULE, T is the message expiration time

pi = Prob(Di ≤ T),

bus network scenario
Bus Network Scenario
  • Simulation Setup
    • Radio bandwidth 400kbps, radio range 100m
    • 20 messages of size 10kb, sent randomly every hour for 12 hours
    • bus storage 1Mb
    • Message expiration time 6 hours
    • Paths are multi-hop
sensor network scenario
Sensor Network Scenario
  • Simulation Setup
    • Nodes placed in 40x16 foot grid, grid size 8ft
related work
Related Work
  • Portfolio Theory
    • Theory used to optimize the Sharpe-ratio
  • Waterfilling in Gaussian channels
    • Formulation uses convex optimization techniques
  • FEC, Erasure Coding, Internet Routing
    • Choice of erasure code
  • Combinatorial Optimization
    • Computes Prob(Y>c) for a given configuration
summary
Summary
  • Problem of reliable transmission in DTN
  • Replication and erasure code for increasing reliability
  • Formulate the optimal allocation problem
  • Study of this problem for Bernoulli and partial path failures
  • Evaluation of the analysis in three different scenarios
slide24
Strengths:
    • Use of erasure coding and replication in DTN
    • Performed extensive analysis of the optimal allocation problem
    • The idea presented in generic and can be applied in other fields too
  • Weakness:
    • Computations involved are complex and may not feasible
    • The study is applicable for probabilities which remain constant over time
    • In partial path failure analysis, it is assumed that the path probabilities have comparable mean and variance. This might not be always true
future development
Future Development
  • Apply this analysis to other fields such as replication of objects in distributed system
  • Develop an efficient method for allocation in Bernoulli path failures
  • Theoretical analysis for choosing replication factor
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