Forward and Reverse message encoding for bacteria nanonetworks

Transcription

1 Forward and Reverse message encoding for bacteria nanonetworks Vitaly Petrov 1, Sasitharan Balasubramaniam 1, Yevgeni Koucheryavy 1, Mikael Skurnik 2 Nano Communications Center (TUT-NCC) 1 Tampere University of Technology Department of Bacteriology and Immunology 2 University of Helsinki

2 Outline 1 Motivation for research in nano communications Nanotechnology 2 Bacteria nanonetworks Baseline model Bacteria movements model 3 Proposed model Bacteria conjugation Cooperative transmission approaches Forward and Reverse message encoding 4 Network analysis Proposed methodology Wet laboratory description Systems analysis

3 Motivation for Research in Nano Communications Nanotechnology a growing and attractive area Applications: biomedical environmental energy military etc. But nanomachines are inherently small and simple. Complex processing is impossible. So the cooperation is required. Nano communications enabling technology for nanomachines to efficiently solve their tasks* *I. F. Akylidiz, F. Brunetti, and C. Blazquez, Nanonetworking: A communication paradigm, Computer Networks, vol. 52, June 2008

4 Bacteria Nanonetworks. Overview Bio Nanomachine Bacteria cell Message! encoded plasmid of bacteria

5 Bacteria Nanonetworks. Baseline Model Bacteria a message carrier object Moving randomly after being released in the area Transmission algorithm (basic): 1. Encode the message into plasmid 2. Bacterium picks up the plasmid 3. Release the bacterium Wired networks Wireless networks Bacteria nanonetworks Unicast Broadcast Any cast

6 Bacterium Movements Model* Straight movement = exponential distribution (E = 3.5 sec) Speed = 20 mcm / sec Turn angle = uniformly distributed [0:2P) *Z. Wang, M. Kim, and G. Rosen, Validating models of bacterial chemo- taxis by simulating the random motility coefficient, in Proceedings of 8th IEEE International Conference on BioInformatics and BioEngineering, 2008

7 Baseline Model Extension Transmission algorithm (extended): 1 Encode the message into plasmid 2 The set of bacteria pick up the plasmid 3 Release the bacteria However, on medium and long range distances (more that 1 mm) even a set of bacteria may not reach the destination...

8 Bacteria Conjugation Mechanism of plasmid exchange between bacteria Pili Plasmid copy Plasmids Nanomachine A Bacteria Nanomachine B Can be applied to increase the number of bacteria with encoded plasmid

9 Cooperative Transmission Approaches Conventional relay node usage Our approach Analyzed in S. Balasubramaniam, P. Lio, Multi- Fixed density of hop Conjugation based Bacteria Nanonetworks", empty bacteria IEEE Transactions on NanoBioscience, 2013 Limitations: Benefits: - Time and location sync up + No time or location sync up is required is required - Low (bacteria) reuse factor + High (bacteria) reuse factor

10 Problems with Multiple Conjugation Due to non-stable connection during conjugations, not the whole message can be copied

11 Forward and Reverse Message Encoding Technique We propose the message encoding technique to mitigate problems with multiple conjugations + Easy to implement in nanomachine + Improves network performance

12 Proposed Methodology for Bacteria Nanonetworks Analysis Applied tools: Experiments in wet laboratory to estimate conjugation characteristics Developed from scratch System-Level Simulator (SLS) to capture environment dynamics Metrics: Probability of success message delivery: This is the probability of delivering at least one bacterium of N within a specified time-to-live interval (T ) Conditional end-to-end delay: The end-to-end delay is the time interval between the bacteria being released from the source nanomachine till the time a full message is successfully decoded at the destination nanomachine, if the message was delivered and successfully decoded

13 Experiments of Bacteria Conjugation Conjugation is inherently difficult -CRISPRimmunesystem -Highlydependentonusedplasmids Experiments conducted at Yersinia Lab, University of Helsinki (Prof. Mikael Skurnik) - E.coli were used as donor and Yersinia pseudotuberculosis were used as recipients -27Kbpplasmids -From to bacteria/ml Experiment results: Time (min) Conjugation frequency

14 Systems Analysis. Overview Models: 1 Baseline system (No Conjugation) 2 Enhanced system (Conjugation) 3 Proposed feature for enhanced system (Conjugation + Coding) Principal parameters: 1 Distance between nodes [0.. 5 mm] 2 Node size 100µ 3 Amount of bacteria per message N=[1.. 20] 4 Density of uncoded (empty) bacteria 1e 5 (10 empty bacteria in 1 mm 2 )

15 Baseline System Analysis (1) Time-To-Live = 24 hours Time-To-Live = 24 hours N = 20 N = 10 N = 5 N = 1 10 N = 20 N = 10 N = 5 N = Probability of successful decoding Conditional end-to-end delay (hours) Distance (mm) Distance (mm) Success probability ( capacity ) is a function of time-to-live (!) More representative graph is required...

16 Baseline System Analysis (2) 1000 mcm distance 5000 mcm distance N = 20 (No conj) N = 10 (No conj) N = 5 (No conj) N = 1 (No conj) N = 20 (No conj) N = 10 (No conj) N = 5 (No conj) N = 1 (No conj) 1 1 Delivered info (share) Delivered info (share) Time (hours) Time (hours) Performance decreases significantly with distance (!) Some improvements to the system are needed...

17 Proposed systems analysis 3000 mcm distance N = 10 (No conj) N = 10 (Conj, d = 1e-5) N = 10 (Conj+Coding, d = 1e-5) 5000 mcm distance N = 10 (No conj) N = 10 (Conj, d = 1e-5) N = 10 (Conj+Coding, d = 1e-5) 1 1 Delivered info (share) Delivered info (share) Time (hours) Time (hours) Up to 30 % gain with conjugation Up to 50 % gain with conjugation + Forward and Reverse coding

18 Conclusions Motivation behind: Nanotechnology has led to development of miniature devices Nano communications provide extra functionality for nanomachines Bacteria nanonetworks - one form of communications, that utilized bacteria as carrier Problem statement: Analysis: Conjugation can lead to partial plasmid delivery Results of experiments in wet laboratory show accurate conjugation characteristics Forward and Reverse message encoding protocol was proposed to mitigate partial plasmid delivery issue Solution was compared with conventional approach via our SLS + Proposed feature improves end-to-end delay and reliability of bacteria nanonetworks