Peer-to-Peer Energy-Aware Tree Network Formation

ABSTRACT

We study the fundamental problem of distributed energy-aware network formation with mobile agents of limited computational power that have the capability to wirelessly transmit and receive energy in a peer-to-peer manner. Specifically, we design simple distributed protocols consisting of a small number of states and interaction rules for the construction of both arbitrary and binary trees. Further, we theoretically and experimentally evaluate a plethora of energy redistribution protocols that exploit different levels of knowledge in order to achieve desired energy distributions which require, for instance, that every agent has twice the energy of the agents of higher depth (according to the tree network). Our study shows that without using any knowledge about the network structure, such energy distributions cannot be achieved in a timely manner, which means that there might be high energy loss during the redistribution process. On the other hand, only a few extra bits of information seem to be enough to guarantee quick convergence to energy distributions that satisfy particular properties, yielding low energy loss.

References

1. C. M. Angelopoulos, J. Buwaya, O. Evangelatos, and J. D. P. Rolim. 2015. Traversal strategies for wireless power transfer in mobile Ad-Hoc networks. In Proceedings of the 18th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM). 31--40.
2. D. Angluin, J. Aspnes, D. Eisenstat, and E. Ruppert. 2007. The computational power of population protocols. Distributed Computing, Vol. 20, 4 (2007), 279--304.
3. S. Bi, Y. Zeng, and R. Zhang. 2016. Wireless powered communication networks: An overview. IEEE Wireless Communications, Vol. 23, 2 (2016), 10--18.
4. E. Bulut, S. Hernandez, A. Dhungana, and B. Szymanski. 2018. Is Crowdcharging Possible?. In Proceedings of the 27th IEEE International Conference on Computer Communications and Networks (ICCN). to appear.
5. H. Dai, Y. Liu, G. Chen, X. Wu, T. He, A. X. Liu, and Y. Zhao. 2018a. SCAPE: Safe Charging With Adjustable Power. IEEE/ACM Transactions on Networking, Vol. 26, 1 (2018), 520--533.
6. H. Dai, H. Ma, A. X. Liu, and G. Chen. 2018b. Radiation Constrained Scheduling of Wireless Charging Tasks. IEEE/ACM Transactions on Networking, Vol. 26, 1 (2018), 314--327.
7. M. del Prete, A. Costanzo, A. Georgiadis, A. Collado, D. Masotti, and Z. Popovi$acutec$. 2015. Energy-autonomous Bi-directional Wireless Power Transmission (WPT) and energy harvesting circuit. In IEEE MTT-S International Microwave Symposium .
8. A. Dhungana, T. Arodz, and E. Bulut. 2018. Charging Skip Optimization with Peer-to-Peer Wireless Energy Sharing in Mobile Networks. In Proceedings of IEEE International Conference on Communications (ICC). to appear.
9. A. Kurs, A. Karalis, R. Moffatt, J. D. Joannopoulos, P. Fisher, and M. Soljav cić. 2007. Wireless power transfer via strongly coupled magnetic resonances. Science, Vol. 317, 5834 (2007), 83--86.
10. M. Lin, M. Gong, B. Lu, Y. Wu, D. Wang, M. Guan, M. Angell, C. Chen, J. Yang, B. J. Hwang, and H. Dai. 2015. An ultrafast rechargeable aluminium-ion battery. Nature, Vol. 520 (2015).
11. A. Madhja, S. Nikoletseas, C. Raptopoulos, and D. Tsolovos. 2016b. Energy Aware Network Formation in Peer-to-Peer Wireless Power Transfer. In The 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM) .
12. A. Madhja, S. E. Nikoletseas, and T. P. Raptis. 2015. Distributed wireless power transfer in sensor networks with multiple mobile chargers. Computer Networks, Vol. 80 (2015), 89--108.
13. A. Madhja, S. E. Nikoletseas, and T. P. Raptis. 2016a. Hierarchical, collaborative wireless energy transfer in sensor networks with multiple Mobile Chargers. Computer Networks (2016).
14. A. Madhja, S. E. Nikoletseas, D. Tsolovos, and A. A. Voudouris. 2018b. Peer-to-Peer Energy-Aware Tree Network Formation. CoRR, Vol. abs/1805.08755 (2018).
15. A. Madhja, S. E. Nikoletseas, and A. A. Voudouris. 2018a. Mobility-aware, adaptive algorithms for wireless power transfer in ad hoc networks. CoRR, Vol. abs/1802.00342 (2018).
16. O. Michail and P. G. Spirakis. 2016. Simple and efficient local codes for distributed stable network construction. Distributed Computing, Vol. 29, 3 (2016), 207--237.
17. S. Nikoletseas, T. P. Raptis, A. Souroulagkas, and D. Tsolovos. 2017b. Wireless Power Transfer Protocols in Sensor Networks: Experiments and Simulations. Journal of Sensor and Actuator Networks, Vol. 6, 2 (2017), 4.
18. S. E. Nikoletseas, T. P. Raptis, and C. Raptopoulos. 2017a. Wireless charging for weighted energy balance in populations of mobile peers. Ad Hoc Networks, Vol. 60 (2017), 1--10.
19. S. E. Nikoletseas, Y. Yang, and A. Georgiadis (Eds.). 2016. Wireless power transfer algorithms, technologies and applications in ad hoc communication networks .Springer.
20. S. Schafer, M. Coffey, and Z. Popovi$acutec$. 2015. X-band wireless power transfer with two-stage high-efficiency GaN PA/ rectifier. In WPTC .
21. S. Zhang, J. Wu, and S. Lu. 2012. Collaborative Mobile Charging for Sensor Networks. In MASS .

Index Terms

• Networks

  • Network properties

    • Network manageability

    • Network structure