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Harmony: Saving Concurrent Transmissions from Harsh RF Interference

Cited 11 time in Web of Science Cited 15 time in Scopus
Authors

Ma, Xiaoyuan; Zhang, Peilin; Liu, Ye; Boano, Carlo Alberto; Kim, Hyung-Sin; Wei, Jianming; Huang, Jun

Issue Date
2020-07
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
Proceedings - IEEE INFOCOM, Vol.2020-July, pp.1024-1033
Abstract
© 2020 IEEE.The increasing congestion of the RF spectrum is a key challenge for low-power wireless networks using concurrent transmissions. The presence of radio interference can indeed undermine their dependability, as they rely on a tight synchronization and incur a significant overhead to overcome packet loss. In this paper, we present Harmony, a new data collection protocol that exploits the benefits of concurrent transmissions and embeds techniques to ensure a reliable and timely packet delivery despite highly congested channels. Such techniques include, among others, a data freezing mechanism that allows to successfully deliver data in a partitioned network as well as the use of network coding to shorten the length of packets and increase the robustness to unreliable links. Harmony also introduces a distributed interference detection scheme that allows each node to activate various interference mitigation techniques only when strictly necessary, avoiding unnecessary energy expenditures while finding a good balance between reliability and timeliness. An experimental evaluation on real-world testbeds shows that Harmony outperforms state-of-the-art protocols in the presence of harsh Wi-Fi interference, with up to 50% higher delivery rates and significantly shorter end-to-end latencies, even when transmitting large packets.
ISSN
0743-166X
URI
https://hdl.handle.net/10371/202139
DOI
https://doi.org/10.1109/INFOCOM41043.2020.9155423
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Research Area Distributed machine learning, Edge, Mobile AI

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