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Communications and Energy-
Harvesting in NanosensorNetworks
                   Michele C. Weigle
    Intelligent Networking and Systems Lab (iNetS)
            Department of Computer Science
                Old Dominion University
                      Norfolk, VA

     NSF Workshop on Biological Computations and Communications
                         November 9, 2012
My Background
• Vehicular Networking
      – the use of vehicles as sensors to
        detect traffic incidents on the road

• Sensor Networks for Emergency
  Assistance
      – re-tasking existing sensor networks
        for use in emergency situations
      – investigating energy issues


November 9, 2012   NSF Workshop on Biological Computation and Communications   2
Why Not Go Smaller?




November 9, 2012   NSF Workshop on Biological Computation and Communications   3
Nanosensor Networks




• Framework articulated by Ian Akyildiz's group at Georgia
  Tech
• Investigated network properties, coding, MAC protocols,
  energy harvesting
• We're just getting started, building on their work
      (many images from Akyildizand Jornet)
November 9, 2012    NSF Workshop on Biological Computation and Communications   4
Applications of Nanosensor
Networks
• Biomedical

• Environmental

• Industrial and
  consumer goods



November 9, 2012   NSF Workshop on Biological Computation and Communications   5
Nanosensor Networks
• Inspired by biological nanoscale
  networks

• Communication
      – molecular
      – electromagnetic - our focus




November 9, 2012   NSF Workshop on Biological Computation and Communications   6
Electromagnetic Communication
• Graphene-based
  nanoantenna
      – graphenenanoribbons
        (GNR) formed by
        unzipping carbon
        nanotubes (CNT)
                                                  http://www.jmtour.com/images/NatureUnzippingImages/TubeUnzipping.png




• Radiates waves in the
  terahertz (0.1-10 THz)
  band
November 9, 2012   NSF Workshop on Biological Computation and Communications                                  7
Terahertz Band



                   http://www.utdallas.edu/news/imgs/photos/terahertz-gap-graph-375_1.jpg




• Supports very high transmission rates in the
  short range
      – up to a few terabits per second
      – distances below 1 meter

November 9, 2012          NSF Workshop on Biological Computation and Communications         8
Pulse-Based Communication
• Not feasible to generate high-power carrier
  signal used in classical communications
      – motivates the need for pulse-based communication

• Femtosecond-long pulses (10-15second)
  proposed

• This introduces major changes in classical
  networking protocols

November 9, 2012   NSF Workshop on Biological Computation and Communications   9
Jornet and Akyildiz
TS-OOK                                 IEEE ICC, 2011

(Time Spread On-Off Keying)




• Example Encoding
      – '1' - 100 fs (0.1 picosecond) pulse
      – '0' - silence
      – 50 ps between bits
November 9, 2012   NSF Workshop on Biological Computation and Communications   10
TS-OOK Example
• With femtosecond
  pulses, probability of
  collision is almost
  non-existent
      – senders transmit when
        they have data ready

• With long inter-bit
  times, multiple
  senders can interleave
  transmissions
November 9, 2012   NSF Workshop on Biological Computation and Communications   11
Communication and Power
• Max capacity of nano-battery - 800 pJ

• Transmission of single pulse - 1 pJ

• Reception of a single pulse - 0.1 pJ




November 9, 2012   NSF Workshop on Biological Computation and Communications   12
Message Coding
• Encode the message such that there are more
  0s transmitted than 1s
      – 0 is silence, costs no energy
                                                   original                    3-bit packet
• Code weight                                      (2 bits)                    (weight = 0.25)
      – average portion of 1s                      00                          000
                                                   01                          001
• Lower code weight,                               10                          010
  more bits                                        11                          100


November 9, 2012   NSF Workshop on Biological Computation and Communications                     13
Energy Harvesting
• Nanosensors have the potential to harvest
  energy from their surroundings
      – solar, thermal, electromagnetic, vibration

• Vibration seems to be the best method for
  nanosensors

• Allows nanosensors to re-charge themselves


November 9, 2012   NSF Workshop on Biological Computation and Communications   14
Energy Harvesting
• Time to charge depends on vibration rate
  (needs 2500 cycles to charge)
    – A/C vents (50 Hz) =~ 50 sec
    – human heart beat (1 Hz) =~ 42 min

• Charging time is not linear

• Arrival of energy is not
  predictable in all scenarios


 November 9, 2012   NSF Workshop on Biological Computation and Communications   15
Impact on Communication
• Energy harvesting phase is orders of
  magnitude larger than communication phase

• End-to-end delay
  significantly affected if
  forwarding nodes need
  to recharge before
  forwarding packet

November 9, 2012   NSF Workshop on Biological Computation and Communications   16
Other Limitations
• Limited resources (memory, power) for storage
  and modulation

• Significant molecular absorption of pulses
      – expensive energy needed for retransmission
      – limited resources for error correction

• Dense network scenarios (100 nodes in 1 cm2)
  need special multi-hop design
November 9, 2012   NSF Workshop on Biological Computation and Communications   17
Our Focus
    • Model communications and energy-harvesting
      process

    • Develop and evaluate strategies for coding,
      packet size, bit repetition, and packet
      retransmission to produce efficient and power-
      aware network transmissions

Joint work with PhD student ShahramMohrehkesh and Dr. Stephan Olariu

    November 9, 2012   NSF Workshop on Biological Computation and Communications   18
Our Road Ahead
• We're just at the beginning of our investigation
• Development of customized protocol layers
      – pulse-based communication models
            • coding methods to send fewer 1s
            • error correction/detection methods: repetition, LDPC, hamming
      – energy harvesting-aware
            • MAC protocol
            • packet scheduling
            • packet formation
      – optimized model for throughput and delay, end2end
        delivery, reliability

• Development of simulation environment
November 9, 2012     NSF Workshop on Biological Computation and Communications   19
Communications and
                       Energy-Harvesting in
                       Nanosensor Networks
              Michele C. Weigle
Intelligent Networking and Systems Lab (iNetS)
        Department of Computer Science
            Old Dominion University
                  Norfolk, VA

                  mweigle@cs.odu.edu
               http://www.cs.odu.edu/inets

NSF Workshop on Biological Computations and Communications
                    November 9, 2012

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Communications and Energy-Harvesting in Nanosensor Networks

  • 1. Communications and Energy- Harvesting in NanosensorNetworks Michele C. Weigle Intelligent Networking and Systems Lab (iNetS) Department of Computer Science Old Dominion University Norfolk, VA NSF Workshop on Biological Computations and Communications November 9, 2012
  • 2. My Background • Vehicular Networking – the use of vehicles as sensors to detect traffic incidents on the road • Sensor Networks for Emergency Assistance – re-tasking existing sensor networks for use in emergency situations – investigating energy issues November 9, 2012 NSF Workshop on Biological Computation and Communications 2
  • 3. Why Not Go Smaller? November 9, 2012 NSF Workshop on Biological Computation and Communications 3
  • 4. Nanosensor Networks • Framework articulated by Ian Akyildiz's group at Georgia Tech • Investigated network properties, coding, MAC protocols, energy harvesting • We're just getting started, building on their work (many images from Akyildizand Jornet) November 9, 2012 NSF Workshop on Biological Computation and Communications 4
  • 5. Applications of Nanosensor Networks • Biomedical • Environmental • Industrial and consumer goods November 9, 2012 NSF Workshop on Biological Computation and Communications 5
  • 6. Nanosensor Networks • Inspired by biological nanoscale networks • Communication – molecular – electromagnetic - our focus November 9, 2012 NSF Workshop on Biological Computation and Communications 6
  • 7. Electromagnetic Communication • Graphene-based nanoantenna – graphenenanoribbons (GNR) formed by unzipping carbon nanotubes (CNT) http://www.jmtour.com/images/NatureUnzippingImages/TubeUnzipping.png • Radiates waves in the terahertz (0.1-10 THz) band November 9, 2012 NSF Workshop on Biological Computation and Communications 7
  • 8. Terahertz Band http://www.utdallas.edu/news/imgs/photos/terahertz-gap-graph-375_1.jpg • Supports very high transmission rates in the short range – up to a few terabits per second – distances below 1 meter November 9, 2012 NSF Workshop on Biological Computation and Communications 8
  • 9. Pulse-Based Communication • Not feasible to generate high-power carrier signal used in classical communications – motivates the need for pulse-based communication • Femtosecond-long pulses (10-15second) proposed • This introduces major changes in classical networking protocols November 9, 2012 NSF Workshop on Biological Computation and Communications 9
  • 10. Jornet and Akyildiz TS-OOK IEEE ICC, 2011 (Time Spread On-Off Keying) • Example Encoding – '1' - 100 fs (0.1 picosecond) pulse – '0' - silence – 50 ps between bits November 9, 2012 NSF Workshop on Biological Computation and Communications 10
  • 11. TS-OOK Example • With femtosecond pulses, probability of collision is almost non-existent – senders transmit when they have data ready • With long inter-bit times, multiple senders can interleave transmissions November 9, 2012 NSF Workshop on Biological Computation and Communications 11
  • 12. Communication and Power • Max capacity of nano-battery - 800 pJ • Transmission of single pulse - 1 pJ • Reception of a single pulse - 0.1 pJ November 9, 2012 NSF Workshop on Biological Computation and Communications 12
  • 13. Message Coding • Encode the message such that there are more 0s transmitted than 1s – 0 is silence, costs no energy original 3-bit packet • Code weight (2 bits) (weight = 0.25) – average portion of 1s 00 000 01 001 • Lower code weight, 10 010 more bits 11 100 November 9, 2012 NSF Workshop on Biological Computation and Communications 13
  • 14. Energy Harvesting • Nanosensors have the potential to harvest energy from their surroundings – solar, thermal, electromagnetic, vibration • Vibration seems to be the best method for nanosensors • Allows nanosensors to re-charge themselves November 9, 2012 NSF Workshop on Biological Computation and Communications 14
  • 15. Energy Harvesting • Time to charge depends on vibration rate (needs 2500 cycles to charge) – A/C vents (50 Hz) =~ 50 sec – human heart beat (1 Hz) =~ 42 min • Charging time is not linear • Arrival of energy is not predictable in all scenarios November 9, 2012 NSF Workshop on Biological Computation and Communications 15
  • 16. Impact on Communication • Energy harvesting phase is orders of magnitude larger than communication phase • End-to-end delay significantly affected if forwarding nodes need to recharge before forwarding packet November 9, 2012 NSF Workshop on Biological Computation and Communications 16
  • 17. Other Limitations • Limited resources (memory, power) for storage and modulation • Significant molecular absorption of pulses – expensive energy needed for retransmission – limited resources for error correction • Dense network scenarios (100 nodes in 1 cm2) need special multi-hop design November 9, 2012 NSF Workshop on Biological Computation and Communications 17
  • 18. Our Focus • Model communications and energy-harvesting process • Develop and evaluate strategies for coding, packet size, bit repetition, and packet retransmission to produce efficient and power- aware network transmissions Joint work with PhD student ShahramMohrehkesh and Dr. Stephan Olariu November 9, 2012 NSF Workshop on Biological Computation and Communications 18
  • 19. Our Road Ahead • We're just at the beginning of our investigation • Development of customized protocol layers – pulse-based communication models • coding methods to send fewer 1s • error correction/detection methods: repetition, LDPC, hamming – energy harvesting-aware • MAC protocol • packet scheduling • packet formation – optimized model for throughput and delay, end2end delivery, reliability • Development of simulation environment November 9, 2012 NSF Workshop on Biological Computation and Communications 19
  • 20. Communications and Energy-Harvesting in Nanosensor Networks Michele C. Weigle Intelligent Networking and Systems Lab (iNetS) Department of Computer Science Old Dominion University Norfolk, VA mweigle@cs.odu.edu http://www.cs.odu.edu/inets NSF Workshop on Biological Computations and Communications November 9, 2012

Editor's Notes

  1. waves of visible light oscillate with a period of ~ 2 fs200 fs – the swiftest chemical reactions