en

Willkommen Gast


  • Login
Full load

Artikel
AutorenGabriel Orsini, Wolf Posdorfer, Winfried Lamersdorf
TitelSaving Bandwidth and Energy of Mobile and IoT devices with Link Predictions
Publiziert inJournal of Ambient Intelligence and Humanized Computing
VerlagSpringer
DatumSeptember 2020
Dokumentnummer (ISBN/DOI)10.1007/s12652-020-02557-z
URLhttps://doi.org/10.1007/s12652-020-02557-z
ZusammenfassungUse cases in the Internet of Things (IoT) and in mobile clouds often require the interaction of one or more mobile devices with their infrastructure to provide users with services. Ideally, this interaction is based on a reliable connection between the communicating devices, which is often not the case. Since most use cases do not adequately address this issue, service quality is often compromised. Aimed to address this issue, this paper proposes a novel approach to forecast the connectivity and bandwidth of mobile devices by applying machine learning to the context data recorded by the various sensors of the mobile device. This concept, designed as a microservice, has been implemented in the mobile middleware CloudAware, a system software infrastructure for mobile cloud computing that integrates easily with mobile operating systems, such as Android. We evaluated our approach with real sensor data and showed how to enable mobile devices in the IoT to make assumptions about their future connectivity, allowing for intelligent and distributed decision making on the mobile edge of the network.
Dokumentpdflogo
Andere Formate Din 1501
bibTexLogo