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One flood to route them all: ultra-fast convergecast of concurrent flows over UWB

Published:16 November 2020Publication History

ABSTRACT

Concurrent transmissions (CTX) enable low latency, high reliability, and energy efficiency. Nevertheless, existing protocols typically exploit CTX via the Glossy system, whose fixed-length network-wide floods are entirely dedicated to disseminating a single packet.

In contrast, the system we present here, Weaver, enables concurrent dissemination towards a receiver of different packets from multiple senders in a single, self-terminating, network-wide flood.

The protocol is generally applicable to any radio supporting CTX; the prototype targets ultra-wideband (UWB), for which a reference network stack is largely missing. Our modular design separates the low-level mechanics of CTX from their higher-level orchestration in Weaver. Other researchers can easily experiment with alternate designs via our open-source implementation, which includes a reusable component estimating UWB energy consumption.

Our analytical model and testbed experiments confirm that Weaver disseminates concurrent flows significantly faster and more efficiently than state-of-the-art Glossy-based protocols while achieving higher reliability and resilience to topology changes.

References

  1. https://github.com/d3s-trento/contiki-uwb.Google ScholarGoogle Scholar
  2. M. Baddeley, A. Stanoev, U. Raza, M. Sooriyabandara, and Y. Jin. Competition: Adaptive software defined scheduling of low power wireless networks. In Proc. of EWSN, 2019.Google ScholarGoogle Scholar
  3. M. Brachmann, O. Landsiedel, and S. Santini. Concurrent transmissions for communication protocols in the internet of things. In Proc. of LCN, 2016.Google ScholarGoogle ScholarCross RefCross Ref
  4. T. Chang, T. Watteyne, X. Vilajosana, and P. H. Gomes. Constructive interference in 802.15.4: A tutorial. IEEE Communications Surveys Tutorials, 2019.Google ScholarGoogle Scholar
  5. P. Corbalán and G. P. Picco. Concurrent Ranging in Ultra-wideband Radios: Experimental Evidence, Challenges, and Opportunities. In Proc. of EWSN, 2018.Google ScholarGoogle Scholar
  6. P. Corbalán, G. P. Picco, and S. Palipana. Chorus: UWB Concurrent Transmissions for GPS-like Passive Localization of Countless Targets. In Proc. of IPSN, 2019.Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. DecaWave Ltd. DW1000 Data Sheet, version 2.19, 2017.Google ScholarGoogle Scholar
  8. DecaWave Ltd. DW1000 User Manual, version 2.18, 2017.Google ScholarGoogle Scholar
  9. A. Dunkels, B. Gronvall, and T. Voigt. Contiki - a lightweight and flexible operating system for tiny networked sensors. In Proc. of LCN, 2004.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. A. Dunkels, F. Osterlind, N. Tsiftes, and Z. He. Software-based on-line energy estimation for sensor nodes. In Proc. of EmNets, 2007.Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. F. Ferrari, M. Zimmerling, L. Mottola, and L. Thiele. Low-power Wireless Bus. In Proc. of SenSys, 2012.Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. F. Ferrari, M. Zimmerling, L. Thiele, and O. Saukh. Efficient Network Flooding and Time Synchronization with Glossy. In Proc. of IPSN, 2011.Google ScholarGoogle Scholar
  13. B. Großwindhager et al. Concurrent Ranging with Ultra-Wideband Radios: From Experimental Evidence to a Practical Solution. In Proc. of ICDCS, 2018.Google ScholarGoogle ScholarCross RefCross Ref
  14. B. Großwindhager et al. SnapLoc: An Ultra-Fast UWB-Based Indoor Localization System for an Unlimited Number of Tags. In Proc. of IPSN, 2019.Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. C. Herrmann, F. Mager, and M. Zimmerling. Mixer: Efficient many-to-all broadcast in dynamic wireless mesh networks. In Proc. of SenSys, 2018.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. K. C. Hewage, S. Raza, and T. Voigt. Protecting glossy-based wireless networks from packet injection attacks. In Proc. of MASS, 2017.Google ScholarGoogle ScholarCross RefCross Ref
  17. T. Istomin, A. L. Murphy, G. P. Picco, and U. Raza. Data Prediction + Synchronous Transmissions = Ultra-low Power Wireless Sensor Networks. In Proc. of SenSys, 2016.Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. T. Istomin, M. Trobinger, A. L. Murphy, and G. P. Picco. Interference-Resilient Ultra-Low Power Aperiodic Data Collection. In Proc. of IPSN, 2018.Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. R. Jacob, J. Baechli, R. D. Forno, and L. Thiele. Synchronous transmissions made easy: Design your network stack with baloo. In Proc. of EWSN, 2019.Google ScholarGoogle Scholar
  20. B. Kempke, P. Pannuto, B. Campbell, and P. Dutta. SurePoint: Exploiting Ultra Wideband Flooding and Diversity to Provide Robust, Scalable, High-Fidelity Indoor Localization. In Proc. of SenSys, 2016.Google ScholarGoogle Scholar
  21. O. Landsiedel, F. Ferrari, and M. Zimmerling. Chaos: Versatile and Efficient All-to-all Data Sharing and In-network Processing at Scale. In Proc. of SenSys, 2013.Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. R. Lim, R. Da Forno, F. Sutton, and L. Thiele. Competition: Robust flooding using back-to-back synchronous transmissions with channel-hopping. In Proc. EWSN, 2017.Google ScholarGoogle Scholar
  23. D. Lobba, M. Trobinger, D. Vecchia, T. Istomin, and G. P. Picco. Concurrent transmissions for multi-hop communication on ultra-wideband radios. In Proc. of EWSN, 2020.Google ScholarGoogle Scholar
  24. M. Mohammad and M. C. Chan. Codecast: Supporting Data Driven In-Network Processing for Low-Power Wireless Sensor Networks. In Proc. of IPSN, 2018.Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. B. A. Nahas, S. Duquennoy, and O. Landsiedel. Network-wide Consensus Utilizing the Capture Effect in Low-power Wireless Networks. In Proc. of SenSys, 2017.Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. B. A. Nahas, S. Duquennoy, and O. Landsiedel. Concurrent Transmissions for Multi-Hop Bluetooth 5. In Proc. of EWSN, 2019.Google ScholarGoogle Scholar
  27. F. Sutton, R. Da Forno, D. Gschwend, T. Gsell, R. Lim, J. Beutel, and L. Thiele. The design of a responsive and energy-efficient event-triggered wireless sensing system. In Proc. of EWSN, 2017.Google ScholarGoogle Scholar
  28. M. Suzuki, Y. Yamashita, and H. Morikawa. Low-power, end-to-end reliable collection using glossy for wireless sensor networks. In Proc. of VTC Spring, 2013.Google ScholarGoogle ScholarCross RefCross Ref
  29. D. Vecchia, P. Corbalan, T. Istomin, and G. P. Picco. Playing with Fire: Exploring Concurrent Transmissions in Ultra-wideband Radios. In Proc. of SECON, 2019.Google ScholarGoogle ScholarCross RefCross Ref
  30. T. Wang, H. Zhao, and Y. Shen. An Efficient Single-Anchor Localization Method Using Ultra-Wide Bandwidth Systems. Applied Sciences, 2020.Google ScholarGoogle Scholar
  31. M. Zimmerling, L. Mottola, P. Kumar, F. Ferrari, and L. Thiele. Adaptive real-time communication for wireless cyber-physical systems. ACM Transaction on Cyber-Physical Systems, 2017.Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. One flood to route them all: ultra-fast convergecast of concurrent flows over UWB

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    • Published in

      cover image ACM Conferences
      SenSys '20: Proceedings of the 18th Conference on Embedded Networked Sensor Systems
      November 2020
      852 pages
      ISBN:9781450375900
      DOI:10.1145/3384419

      Copyright © 2020 ACM

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      Publication History

      • Published: 16 November 2020

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