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A QoS-aware Adaptive Mobility Handling Approach for LoRa-based IoT Systems
Katholieke Univ Leuven, Belgium.
Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM). Katholieke Univ Leuven, Belgium.ORCID-id: 0000-0002-1162-0817
2018 (Engelska)Ingår i: 2018 12TH IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2018), IEEE, 2018, s. 130-139Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Internet-of-Things (IoT) is an emergent paradigm that is increasingly applied in smart cities. A popular technology used in IoT is LoRa that supports long-range wireless communication. In this research, we study LoRa-based IoT systems with battery-powered end nodes that collect and communicate data to a gateway for further processing. Existing approaches in such IoT systems usually only consider stationary end nodes. We focus on systems with mobile end nodes, paving the way to new applications such as target tracking. Key Quality of Service (QoS) requirements for these settings are the reliability of the communication and energy consumption. With mobile end nodes, ensuring these QoS is challenging as the system is subject to continuous changes. In this paper, we investigate how the settings of a mobile end node impact key performance indicators for reliability and energy consumption. Based on insights obtained from extensive field experiments, we devise an algorithm that automatically adapts the settings of a mobile end node to ensure its QoS requirements for a setup with a single gateway. We then extend the algorithm to a setup with multiple gateways. We demonstrate how the algorithms achieve the QoS requirements of a mobile end node in a concrete IoT deployment.

Ort, förlag, år, upplaga, sidor
IEEE, 2018. s. 130-139
Serie
International Conference on Self-Adaptive and Self-Organizing Systems, ISSN 1949-3673
Nationell ämneskategori
Data- och informationsvetenskap Signalbehandling
Forskningsämne
Data- och informationsvetenskap, Datavetenskap
Identifikatorer
URN: urn:nbn:se:lnu:diva-81105DOI: 10.1109/SASO.2018.00024ISI: 000459885200014Scopus ID: 2-s2.0-85061896468ISBN: 978-1-5386-5172-8 (tryckt)OAI: oai:DiVA.org:lnu-81105DiVA, id: diva2:1296489
Konferens
12th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO), SEP 03-07, 2018, Trento, ITALY
Tillgänglig från: 2019-03-15 Skapad: 2019-03-15 Senast uppdaterad: 2019-08-29Bibliografiskt granskad

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