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Crowdsourcing low-power wide-area IoT networks

Authors: Keyi Zhang; Alan Marchiori;

Crowdsourcing low-power wide-area IoT networks

Abstract

The Internet of Things (IoT) promises to allow everyday objects to connect to the Internet and seamlessly interact with users and other machines. For this vital Internet connection, most current IoT devices use a personal gateway device such as a smartphone or a home WiFi access point. The necessity of configuring and maintaining these gateways presents an additional burden for both users and developers of IoT applications. Our vision for IoT connectivity is to eliminate the need for the personal gateway by developing crowdsourced low-power wide area networks (csLPWAN). Recent technologies such as RPMA, LoRa, and R-FDMA enable links to reach 15km using ISM-band transceivers, making csLPWANs an attractive option. In this paper, we investigate the practicality of csLPWANs and develop the first csLPWAN planning tool, PlanIt, which combines topography-aware RF signal analysis with demographic data to predict LPWAN coverage in specific geographic areas. Using PlanIt, we find that most cities achieve 99% coverage by deploying a single LPWAN base station within the city. To provide better service on the csLPWAN, we propose and evaluate D-QN, a near-optimal MAC protocol to enable efficient bandwidth sharing in highly utilized networks. In the future, csLPWANs could accommodate a heterogeneous set of IoT applications, simplifying the IoT application development cycle, reducing total system cost, improving application reliability, and enhancing the user experience.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Average
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