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Content-Centric IoT-Based Air Pollution Monitoring

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Abstract

The Internet of Things (IoT) has been attracting a lot of attention due to its extensive applications such as air pollution monitoring. IoT is based on end-to-end communications where each device independently delivers collected data. This leads to a lot of redundant data especially in the air pollution monitoring case where the data collected in a specific area is highly correlated. To suppress data redundancy and alleviate data delivery costs, we propose a Content-centric IoT-based Air pollution Monitoring (CIAM) system. In CIAM, the content-centric mechanism is exploited to perform air pollution data aggregation and delivery. For each type of content, a content-centric backbone is constructed so that the devices involved in the backbone can aggregate the correlated data and lower the data delivery cost and latency. CIAM is quantitatively evaluated, and the results demonstrate that CIAM alleviates the data delivery costs and latency.

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Funding

This work is supported by the CERNET Innovation Project(NGII20170106).

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Authors and Affiliations

  1. Changshu Institute of Technology, Suzhou, China

    Xinyan Qian & Xiaonan Wang

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  1. Xinyan Qian
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  2. Xiaonan Wang
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Contributions

XW has proposed the idea, and XQ and XW have cooperated to verify the feasibility of the idea.

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Correspondence to Xiaonan Wang.

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Qian, X., Wang, X. Content-Centric IoT-Based Air Pollution Monitoring. Wireless Pers Commun 123, 3213–3222 (2022). https://doi.org/10.1007/s11277-021-09284-4

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  • DOI: https://doi.org/10.1007/s11277-021-09284-4

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