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Maximizing Broadcast Throughput under Ultra-Low-Power Constraints

Publication ,  Journal Article
Chen, T; Ghaderi, J; Rubenstein, D; Zussman, G
Published in: IEEE/ACM Transactions on Networking
April 1, 2018

Wireless object-tracking applications are gaining popularity and 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, we formulate 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. We obtain the oracle throughput (i.e., maximum throughput achieved by an oracle) and use Lagrangian methods to design EconCast - a simple asynchronous distributed protocol in which nodes transition between sleep, listen, and transmit states, and dynamically change the transition rates. EconCast can operate in groupput or anyput mode to respectively maximize two alternative throughput measures. We show that EconCast approaches the oracle throughput. The performance is also evaluated numerically and via extensive simulations and it is shown that EconCast outperforms prior art by 6×- 7× under realistic assumptions. Moreover, we evaluate EconCast's latency performance and consider design tradeoffs when operating in groupput and anyput modes. Finally, we implement EconCast using the TI eZ430-RF2500-SEH energy harvesting nodes and experimentally show that in realistic environments it obtains 57%-77% of the achievable throughput.

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Published In

IEEE/ACM Transactions on Networking

DOI

ISSN

1063-6692

Publication Date

April 1, 2018

Volume

26

Issue

2

Start / End Page

779 / 792

Related Subject Headings

  • Networking & Telecommunications
  • 4606 Distributed computing and systems software
  • 4006 Communications engineering
  • 1005 Communications Technologies
  • 0906 Electrical and Electronic Engineering
  • 0805 Distributed Computing
 

Citation

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Chen, T., Ghaderi, J., Rubenstein, D., & Zussman, G. (2018). Maximizing Broadcast Throughput under Ultra-Low-Power Constraints. IEEE/ACM Transactions on Networking, 26(2), 779–792. https://doi.org/10.1109/TNET.2018.2805185
Chen, T., J. Ghaderi, D. Rubenstein, and G. Zussman. “Maximizing Broadcast Throughput under Ultra-Low-Power Constraints.” IEEE/ACM Transactions on Networking 26, no. 2 (April 1, 2018): 779–92. https://doi.org/10.1109/TNET.2018.2805185.
Chen T, Ghaderi J, Rubenstein D, Zussman G. Maximizing Broadcast Throughput under Ultra-Low-Power Constraints. IEEE/ACM Transactions on Networking. 2018 Apr 1;26(2):779–92.
Chen, T., et al. “Maximizing Broadcast Throughput under Ultra-Low-Power Constraints.” IEEE/ACM Transactions on Networking, vol. 26, no. 2, Apr. 2018, pp. 779–92. Scopus, doi:10.1109/TNET.2018.2805185.
Chen T, Ghaderi J, Rubenstein D, Zussman G. Maximizing Broadcast Throughput under Ultra-Low-Power Constraints. IEEE/ACM Transactions on Networking. 2018 Apr 1;26(2):779–792.

Published In

IEEE/ACM Transactions on Networking

DOI

ISSN

1063-6692

Publication Date

April 1, 2018

Volume

26

Issue

2

Start / End Page

779 / 792

Related Subject Headings

  • Networking & Telecommunications
  • 4606 Distributed computing and systems software
  • 4006 Communications engineering
  • 1005 Communications Technologies
  • 0906 Electrical and Electronic Engineering
  • 0805 Distributed Computing