TY  - GEN
A1  - Sahlmann, Kristina
A1  - Scheffler, Thomas
A1  - Schnor, Bettina
T1  - Ontology-driven Device Descriptions for IoT Network Management
T2  - 2018 Global Internet of Things Summit (GIoTS)
N2  - One particular challenge in the Internet of Things is the management of many heterogeneous things. The things are typically constrained devices with limited memory, power, network and processing capacity. Configuring every device manually is a tedious task. We propose an interoperable way to configure an IoT network automatically using existing standards. The proposed NETCONF-MQTT bridge intermediates between the constrained devices (speaking MQTT) and the network management standard NETCONF. The NETCONF-MQTT bridge generates dynamically YANG data models from the semantic description of the device capabilities based on the oneM2M ontology. We evaluate the approach for two use cases, i.e. describing an actuator and a sensor scenario.
KW  - Internet of Things
KW  - Interoperability
KW  - oneM2M
KW  - Ontology
KW  - Semantic Web
KW  - NETCONF
KW  - YANG
KW  - MQTT
Y1  - 2018
SN  - 978-1-5386-6451-3
U6  - https://doi.org/10.1109/GIOTS.2018.8534569
SP  - 295
EP  - 300
PB  - IEEE
CY  - New York
ER  - 
TY  - GEN
A1  - Sahlmann, Kristina
A1  - Schwotzer, Thomas
T1  - Ontology-based virtual IoT devices for edge computing
T2  - Proceedings of the 8th International Conference on the Internet of Things
N2  - An IoT network may consist of hundreds heterogeneous devices. Some of them may be constrained in terms of memory, power, processing and network capacity. Manual network and service management of IoT devices are challenging. We propose a usage of an ontology for the IoT device descriptions enabling automatic network management as well as service discovery and aggregation. Our IoT architecture approach ensures interoperability using existing standards, i.e. MQTT protocol and SemanticWeb technologies. We herein introduce virtual IoT devices and their semantic framework deployed at the edge of network. As a result, virtual devices are enabled to aggregate capabilities of IoT devices, derive new services by inference, delegate requests/responses and generate events. Furthermore, they can collect and pre-process sensor data. These tasks on the edge computing overcome the shortcomings of the cloud usage regarding siloization, network bandwidth, latency and speed. We validate our proposition by implementing a virtual device on a Raspberry Pi.
KW  - Internet of Things
KW  - Edge Computing
KW  - oneM2M Ontology
KW  - M2M
KW  - Semantic Interoperability
KW  - MQTT
Y1  - 2018
SN  - 978-1-4503-6564-2
U6  - https://doi.org/10.1145/3277593.3277597
SP  - 1
EP  - 7
PB  - Association for Computing Machinery
CY  - New York
ER  -