we discuss devops requirements for dynamic interoperability in IoT Cloud software systems

1. DevOps for Dynamic
Interoperability of IoT, Edge
and Cloud Systems
Hong-Linh Truong,
Department of Computer Science
http://rdsea.github.io

2. Diversity and Complexity in
Developing IoT Cloud applications
❏Cloud resources
❏ Datahub, message brokers, databases, analytics, etc.
❏ Such resources can be requested on-demand
❏Edge and network functions resources
❏ Firewall, lightweight brokers, storage, edge AI, etc.
❏ Software-based network functions, deployed on-demand using cloud technologies
❏IoT resources
❏ Sensors, Actuator, IoT Gateways, IoT platforms, etc.
2nd Vienna Software Seminar (VSS), 30 August 2019
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All (multi-layered cross-
systems) resources are
(micro) services

3. Interoperability issues
❏ On IoT/edge side
❏ devices integration, sensor connectivity, sensor data models, discovery,
etc.
❏ Interoperability among Things, within an IoT/edge platform
❏ On (public/private) services in data centers for IoT
❏ Protocol and data integration, data transformation, etc.
❏ Interoperability in accessing multiple IoT platforms
❏ On both IoT and cloud sides
❏ Platform to platform, IoT middleware, IoT-Edge-Cloud
❏ Interoperability across multiple IoT platforms
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4. Complex case: example of SeaPort
Interoperability issues: Data format, data semantics,
APIs, middleware services, and regulations
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Based on the H2020 EU INTER-IoT project -http://www.inter-iot-project.eu/

5. Example: Protocol bridges and other
services
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Protocol bridge
Platform
IoT platform
Resource discovery
and provisioning

6. Example: activities and runtime
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Development
Operation: IoT
Cloud
application

7. DevOps for dynamic interoperability
▪ Developments
▪ Artifacts for interoperability
▪ Searching software artefact and automatic deployment of
software across IoT, edge and cloud
▪ Artifacts can be instantiated into the right environments
▪ E.g., a middleware service for performing protocol translation, a data
pipeline for covering data, or a function for filtering IoT data
▪ Operations
▪ Resource providers for IoT, edge and cloud resources
▪ Resource ensembles elasticity and composition at runtime
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8. Overall process
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Development using existing
tools/methods
Kubernetes, Docker, etc. in
Edge+Cloud
Resource ensemble
across edge+cloud
Dynamic provisioning,
Elasticity, & service
mesh
New types of metadata for
multi-faced interoperability

9. Prototypes and testbed
❏Current working prototypes
❏ rsiHub: https://github.com/SINCConcept/HINC/
❏ IoTCloudSamples: https://github.com/rdsea/IoTCloudSamples
❏Testbed
❏ Google Cloud and Edge devices
❏ for Cloud services and for emulating edge/IoT platforms
❏ for emulating IoT sensors
❏Realistic dataset or emulating dataset for sensors
❏Real service providers and emulating services for application
domains
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10. Thanks!
Hong-Linh Truong
Department of Computer Science
rdsea.github.io
2nd Vienna Software Seminar (VSS), 30 August 2019
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