1 / 25

Recovering Data F rom Corrupt Packets

Recovering Data F rom Corrupt Packets. Sensys 2013 EWSN 2014. T ypical procedure of transmission. Techniques for overcoming bit errors ARQ : Automatic Repeat reQuest FEC : Forward Error Correction Or the combination : HARQ

daisy
Download Presentation

Recovering Data F rom Corrupt Packets

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Recovering Data From Corrupt Packets Sensys 2013 EWSN 2014

  2. Typical procedure of transmission • Techniques for overcoming bit errors • ARQ : Automatic Repeat reQuest • FEC : Forward Error Correction • Or the combination : HARQ • Interesting things happened when it finds a corrupted packet during the CRC detection process! • All IS NOT LOST(ANL): a opportunistic approach • TVA: an novel method of CRC correcting

  3. DSSS in 802.15.4 Standard • A byte = 2 four-bit symbols • Echo symbol is finally represented by a 32-bit log chip sequence (i.e. the rightmost table) • What happened when takes noise into consideration ? • Corruption may happen

  4. ANL : Observation • Deployment • 16 nodes • One year from 2012 to 2013 • Mutation Matrix: • Each entry denotes a mutation frequency • One Observation: • Mutations are not uniformly distributed

  5. ANL : Recovering Data • Consider a received symbol • E.g s13,p(s5|s13)= • Consider a received sequence of symbols • E.g receive symbol sequence r = (s13,s3,s0,s11) • a possible sent sequence t = (s5,s3,s1,s11) • Key idea: compute a probability distribution over the possible sent packets

  6. ANL : Left questions • How to generate the mutation matrix? • Through Simulation • How to estimate pchip : using LQI • Is the actual sent word is assigned the highest rank?(95% of them are)

  7. TVA-A reliable protocol • Procedure • Feature: • A novel method of CRC error correction • Compact and computationally efficient • Designed to correct the most common error patterns observed in WSNs

  8. CRC error correction Theory • Tabular Method • m2 - the received msg; m1 – the sent msg ; e – the error pattern we want to correct • Prebuild a table using CRCs of target error pattern P as index • Index into the table with c and get error sequence e.The corrected message • Cyclic Method • anyway,reduced memory requirement needed by single Tabular Method • e.g 64 bytes to correct 4-bit-bursts in 40 bytes of data , while the tabular method uses 10KB

  9. Reliability of TVA:verify • Correction process:m1 • Risk : if CRC(e1) = CRC(e2) and • Verify : compare the sender side CRC and receiver side CRC • So what is this polynomial P? • Not the correcting polynomial G : since CRC(m1 e1 e2 ) = CRC(m1) CRC(e1) CRC(e2) = CRC(m1) • The key property of the polynomial P : it does not fail to detect a message error consisting of a common channel error XOR’d with a correction error e2

  10. Searching for Polynomials:results

  11. Performance Comparison

  12. Conclusion of two work • Solve the same issue • Recovering information from corrupt packet • Different method • ANL : a probabilistic approach • TVA : CRC error correcting • Combination Possibility?

  13. 谢谢!

  14. Comparison with other protocol

  15. Outline 1.All is not lost the distinct pattern of how 802.15.4 packets are corrupted an probabilistically approach infers the original content of a corrupt packet 2.Unlocking the full power of the CRC a novel method of CRC error correction a protocol TVA making use of the error correcting ability of CRC

  16. Comparision with ANL

  17. Observations • Observation 1:Mutations are not uniformaly distributed • Observation 2:The most significant bit of a symbol is more stable than other bits • Observation 3:Symbols s0 to s7 are more stable than other symbols

  18. Explanation

  19. Exploitation Compute a distribution:

More Related