Ontology-based Virtual IoT Devices for Edge Computing The 8th - - PowerPoint PPT Presentation

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Ontology-based Virtual IoT Devices for Edge Computing The 8th - - PowerPoint PPT Presentation

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Ontology-based Virtual IoT Devices for Edge Computing The 8th International Conference on the Internet of Things (IoT 2018) Santa Barbara, California, USA October 1518, 2018 Kristina Sahlmann , Thomas Schwotzer Heterogeneity of network

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Ontology-based Virtual IoT Devices for Edge Computing

The 8th International Conference on the Internet of Things (IoT 2018) Santa Barbara, California, USA October 15–18, 2018 Kristina Sahlmann, Thomas Schwotzer

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Heterogeneity of network devices

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Source: https://goo.gl/images/tyaQo1

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Idea

  • aggregate self-descriptive devices at the edge of

the network

  • furthermore
  • derive new services
  • delegate requests/responses
  • collect and pre-process sensor data
  • generate events

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Definition: Virtual Device

  • no actuators and no sensors onboard
  • deployed at the edge of the network
  • hides real devices (information hiding principle)
  • aggregate capabilities of real devices
  • offer aggregated capabilities

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System Architecture

  • f a Virtual Device

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Device 1 Device 2 Virtual Device

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Topology of Virtual Devices

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Virtual Device 1 Virtual Device 2 Virtual Device Building Mobile Client Client Floor 1 Floor 2

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Operations and Tasks

  • f Virtual Devices
  • Scenario 1: Semantic Deployment
  • collect and aggregate device capabilities from device

descriptions

  • infer new system capabilities from device descriptions
  • generate a virtual device description
  • publish this description e.g. to the MQTT broker
  • e.g. define a new aggregated capability

“switch off all lights in the 1st floor”

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Operations and Tasks

  • f Virtual Devices
  • Scenario 2: Controlling and Measuring Services
  • map aggregated functionalities to the single device

functionality

  • delegate controlling and measuring functionalities
  • e.g. execute a controlling service

“switch off all lights in the 1st floor”

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Operations and Tasks

  • f Virtual Devices
  • Scenario 3: Aggregation of Sensor Data
  • collect and pre-process sensor data
  • aggregate sensor data
  • calculate average value
  • e.g. calculate an average temperature in the 1st

floor per hour

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Operations and Tasks

  • f Virtual Devices
  • Scenario 4: Alarm/Event Trigger
  • monitor sensor data
  • prove conditions
  • create push events
  • trigger alarms if necessary
  • e.g. raise alarm when temperature is over 30° Celcius

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Software components of a virtual device

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Implementation Scope

  • Scenario 1: Semantic Deployment
  • Scenario 2: Controlling and Measuring Services

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Gap between the generic oneM2M and specific Device Ontology

  • neM2M Ontology

Device Description

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GAP

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Extended

  • neM2M

Ontology 1st level

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Extended

  • neM2M

Ontology 2nd level

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Inference possibilities

  • oneM2M ontology is defined in OWL 2 DL flavour
  • OWL constructs:

<owl:Restriction>,<owl:someValuesFrom>, <owl:sameAs>, <owl:equivalentClass>, etc.

  • SWRL rules
  • SPARQL requests

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OWL Abstract Class for switchOff Functionality

<owl:Class rdf:about="service#AbstractSwitchOffFunctionality"> <rdfs:subClassOf rdf:resource="onem2m#ControllingFunctionality"/> <rdfs:subClassOf> <owl:Restriction> <owl:onProperty rdf:resource="ext-onem2m#hasControllingFunctionality"/> <owl:someValuesFrom> <owl:Class> <owl:oneOf rdf:parseType="Collection"> <onem2m#ControllingFunctionality rdf:about="dev#switchOff"/> <onem2m#ControllingFunctionality rdf:about="dev#turnOff"/> </owl:oneOf> </owl:Class> </owl:someValuesFrom> </owl:Restriction> </rdfs:subClassOf> </owl:Class>

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SWRL Rule for switchOff Functionality

  • nem2m:Device(?d)

^ service:hasControllingFunctionality(?d, ?f) ^ swrlb:containsIgnoreCase(?f, "switchOff")

  • > AbstractSwitchOffFunctionality(?f)
  • nem2m:Device(?d)

^ service:hasControllingFunctionality(?d, ?f) ^ swrlb:containsIgnoreCase(?f, "turnOff")

  • > AbstractSwitchOffFunctionality(?f)

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SPARQL Request for switchOff Functionality

PREFIX onem2m: <http://www.onem2m.org/ontology/Base_Ontology/base _ontology#> SELECT ?functionality ?type WHERE { ?functionality rdf:type owl:NamedIndividual. ?functionality rdf:type

  • nem2m:ControllingFunctionality.

FILTER REGEX (?functionality, „off", "i"). }

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Implementation

  • Python, RDFLib incl. SPARQL
  • No Python Implementation of SWRL
  • Virtual Device on Raspberry Pi 3B

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Evaluation on IoT Devices

  • CC2538 Development Kit from Texas Instruments
  • Light Sensor
  • Led
  • 6LoWPAN
  • Arduino Yún Rev 2
  • Light Sensor
  • Humidity Sensor
  • Relay
  • Wi-Fi

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Conclusion on Virtual Device

  • information hiding principle
  • reduce complexity
  • aggregate capabilities of real devices
  • scalable architecture
  • model-driven

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Conclusion on Ontology

  • oneM2M Base ontology must be extended
  • only core vocabulary/schema is not enough
  • describe the capabilities not only things (how vs. what)
  • further classification of things and functionalities

needed, e.g. subclasses, abstract classes, patterns

  • but leave space on customization

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Thank you! Any questions?

Kristina Sahlmann sahlmann@uni-potsdam.de sahlmann@htw-berlin.de

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An ontology-based NETCONF-MQTT bridge

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Introduced at InterOSS-IoT 2018, Bilbao, Spain