Research on Nanonetworking

  • End-to-end Wireless Path Deployment with Intelligent Surfaces Using Interpretable Neural Networks
    C Liaskos, S Nie, A Tsioliaridou, A Pitsillides, S Ioannidis, I Akyildiz
    IEEE Transactions on Communications

NanoNetworks track


This research track constitutes my secondary research objective, at the TNL Lab, Institute of Computer Science, Foundation for Research and Technology - Hellas, Greece. 


Introduction: Nanonetworks

Advances in nanotechnology have enabled the extension of control and networking to micro/nano scales. The RFID dust by Hitachi Ltd., for example, comprises nodes that are manufactured at a total size of 0.153 mm. Graphene technology is expected to enable the further miniaturization of wireless antennas and modules operating at the THz band.

(Figure: RFID schips next to a human hair.)

Nanonetworking promises interesting applications in a variety of fields:

  • In biomedicine, nano-devices are envisioned to monitor the human body at cellular level, and perform targeted drug delivery.
  • In the materials and environmental monitoring industry, nanonetworking enables the construction of smart, active materials, which enable the real-time monitoring of their internal structural, or even the control over their electromagnetic behavior. Such components are expected to extend the reach of IoT to the level of material properties. 

The Objective: Nano-Data Routing Schemes

Data routing in nanonetworks faces new and unique challenges, stemming from the expectedly limited hardware capabilities of the nanonodes. This expectation is enforced by several factors:

  • The miniature size of the nanonodes naturally translates to assembly restrictions.
  • A nanonetwork may contain thousands of nodes, implying a very low-cost nanonode architecture.
  • Despite its low capabilities, the nanonode hardware must face the unique challenges of the THz band, such as high path loss due to molecular absorption, and high ambient noise.

These factors imply that nanonetworking is error-prone, and a routing scheme should offer a good degree of path multiplicity. On the other hand, the nanonode power supply is not abundant, and a data routing scheme should keep redundant transmissions low. An additional routing concern is that nanonode addressing is neither unique nor a given.

The Envisioned Key-Contribution

"A data routing scheme with minimal complexity and great cutomization flexibility.” 

Studied System Aspects

Simulation techniques

  • Ray-tracing-based nanonetwork simulation. Comparison with FDTD [[[kantelis2014use]]][[[meta2016]]]. 

Node addressing and data routing approaches

  • Virtual coordinate-based approaches [[[Tsioliaridou2015SLR]]] [[[Tsioliaridou1n3]]].
  • Nature-inspired approaches [[[Tsioliaridou2016lightweight]]] [[[Liaskosdeployable]]] [[[Liaskos2015promise]]].

Novel applications of nanonetworks

  • Materials with programmable electromagnetic properties. A combination of metamaterials and nanonetworks [[[Liaskos2015design]]]. 
  • This is a joint work with well-known physicists (C. Soukoulis, M. Kafesaki) and network experts (I. F. Akyildiz).

Conclusion

Nanonetworking is a novel, highly promising sub-discipline of computer science, which will extend the reach of IoT at nano-levels. Numerous research opportunities exist in the physical, medium access, networking and application layers.   

Funding

This research has been partially funded by the VirtuWind Project (H2020-5gPP), Contract Number: EU671648.

References

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