Broadband Communications, Networks, and Systems. 9th International EAI Conference, Broadnets 2018, Faro, Portugal, September 19–20, 2018, Proceedings

Research Article

Location-Aware MAC Scheduling in Industrial-Like Environment

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  • @INPROCEEDINGS{10.1007/978-3-030-05195-2_20,
        author={Maurizio Rea and Domenico Garlisi and H\^{e}ctor Cordob\^{e}s and Domenico Giustiniano},
        title={Location-Aware MAC Scheduling in Industrial-Like Environment},
        proceedings={Broadband Communications, Networks, and Systems. 9th International EAI Conference, Broadnets 2018, Faro, Portugal, September 19--20, 2018, Proceedings},
        proceedings_a={BROADNETS},
        year={2019},
        month={1},
        keywords={MAC scheduler Indoor localization system Context awareness},
        doi={10.1007/978-3-030-05195-2_20}
    }
    
  • Maurizio Rea
    Domenico Garlisi
    Héctor Cordobés
    Domenico Giustiniano
    Year: 2019
    Location-Aware MAC Scheduling in Industrial-Like Environment
    BROADNETS
    Springer
    DOI: 10.1007/978-3-030-05195-2_20
Maurizio Rea,*, Domenico Garlisi1, Héctor Cordobés2, Domenico Giustiniano2
  • 1: CNIT and University of Palermo
  • 2: IMDEA Networks Institute
*Contact email: maurizio.rea@imdea.org

Abstract

We consider an environment strongly affected by the presence of metallic objects, that can be considered representative of an indoor industrial environment with metal obstacles. This scenario is a very harsh environment where radio communication has notorious difficulties, as metallic objects create a strong blockage component and surfaces are highly reflective. In this environment, we investigate how to dynamically allocate MAC resources in time to static and mobile users based on context awareness extracted from a legacy WiFi positioning system. In order to address this problem, we integrate our WiFi ranging and positioning system in the WiSHFUL architecture and then define a hypothesis test to declare if the link is in line-of-sight (LOS) or non-line-of-sight (NLOS) based on angular information derived from ranging and position information. We show that context information can help increase the network throughput in the above industrial-like scenario.