Scientific Publication Review

  • 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

IEEE ICT'16(pdf)

by Tsioliaridou A., Liaskos C., Pachis L., Ioannidis S., Pitsillides A.
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This work belongs to the Nanonetworking research track.


N3: Addressing and Routing in 3D Nanonetworks [[[Tsioliaridou1n3]]]

Abstract: Wireless communication at nanoscale faces unique challenges stemming from low hardware capabilities, limited power supply and unreliable channel conditions. The present paper proposes a networking scheme that can operate efficiently under such physical restrictions. Studying 3D multi-hop networks, the novel scheme offers scalable, trilateration-based node addressing and low-complexity packet routing mechanisms. Analysis is employed to design a routing process that balances path multiplicity for robust data delivery, and minimization of redundant transmissions. Extensive simulations yield increased resilience to challenging network conditions. 

In a nutshell

The present paper introduced the N3, an addressing and routing scheme for 3D nanonetworks. N3 addresses each node (gray spheres below) by its distances from a selected set of anchor points:

These distances also define node-bounding volumes, within which packets are routed via multi-hop retransmissions, from a sender P1 to a receiver P2:

 

Key-points

  • Via the volume approach, N3 naturally provides path multiplicity and node failover, which are mandatory in the challenging nano-environment.
  • A triplet of anchors is selected by a sender-node prior to its transmission.
  • Each triplet selection yields a different boudning volume, allowing for optimization of selection.
  • N3 was optimized analytically in terms of minimization of retransmissions, whilst ensuring the high resilience of the network demanded by many applications, e.g. smart materials. 

Acknowledgement

This work was partially supported by the EU Horizon 2020 VirtuWind project (Grant no. EU 671648).


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