Föreläsning 5 - IoT Systems Engineering over the Edge-Cloud Continuum Flashcards
(5 cards)
Deployment topology, everything in the cloud model -
the software components of IoT systems are placed in the Cloud. It is suitable when the systems require significant elastic processing and storage capabilities or when the constituents are scattered in various areas.
Deployment topology, everything in the edge and fog model -
The software components of IoT systems are placed in networks of more constrained devices with respect to the cloud (local servers and gateways) that are at the Edge of the network. In this model, the computational capabilities are lower than those within the cloud-based model.
Deployment topology, hybrid edge-cloud model -
The software components of IoT systems are distributed across the Cloud and the Edge of the network. Thus, it enables exploiting the advantages of the other two models. For instance, it supports deploying the components that should perform processes with low latency in the Edge of the network, and deploying those that perform resource-demanding processes in the Cloud.
Factors determining the fog models -
Data volume reduction (fog models are needed for processing large, unstructured data (e.g., video) in real-time at the edge). Number of edge devices (fog systems scale dynamically with the number of sensors, handling unpredictable or large datasets). Fog node capabilities (fog nodes manage heavy analytics, while edge gateways handle connectivity and safety actions). System reliability (fog nodes ensure reliability by enabling backup nodes to take over in case of failure).
Give an example of an edge platform -
Microsoft Azure Iot Edge. A container-based deployment engine for edge devices running Windows or Linux. It offers an open-source runtime, Docker container platform, API for cloud interface, and provisioning services. It handles tasks like offline operation, local data storage, cloud syncing, data filtering, and security services.