T. Chen, J. Ghaderi, D. Rubenstein, and G. Zussman, “Maximizing broadcast throughput under ultra-low-power constraints,” in Proc. ACM CoNEXT’16, Dec. 2016.
This year ACM CoNEXT (ACM International Conference on emerging Networking EXperiments and Technologies) received 199 submissions and the acceptance ratio was 17.6%.
The paper is motivated by wireless object tracking applications such as the ones envisioned in the EnHANTs project. Such applications will soon utilize emerging ultra-low-power device-to-device communication. However, severe energy constraints require much more careful accounting of energy usage than what prior art provides. In particular, the available energy, the differing power consumption levels for listening, receiving, and transmitting, as well as the limited control bandwidth must all be considered.
Therefore, the paper formulates the problem of maximizing the throughput among a set of heterogeneous broadcasting nodes with differing power consumption levels, each subject to a strict ultra-low-power budget. The oracle throughput (i.e., maximum throughput achieved by an oracle) is obtained and Lagrangian methods are used to design EconCast – a simple asynchronous distributed protocol in which nodes transition between sleep, listen, and transmit states, and dynamically change the transition rates.
It is shown that EconCast approaches the oracle throughput. Moreover, the performance is evaluated numerically and via extensive simulations and it is shown that EconCast outperforms prior art by 6x – 17x under realistic assumptions. Finally, EconCast is implemented using the TI eZ430-RF2500-SEH energy harvesting nodes and it is experimentally shown that in realistic environments it obtains 57% – 77% of the achievable throughput.