engleski

Adaptive Data-Driven Edge-to-Cloud Environment

The concept of Edge-to-Cloud Continuum (ECC) aims to significantly reduce the overall traffic to the cloud by performing the IoT data processing as close as possible to the data sources, either on near- or far-edge devices. In the highly dynamic ECC environment, where IoT devices and edge nodes are constantly changing state and location, services running on edge nodes have to be scheduled, deployed and managed to ensure high service availability with appropriate Quality of Service (QoS) parameters. However, once the services are deployed in the continuum between IoT devices and the cloud, the question arises how to ensure continuous data delivery from IoT devices to the appropriate services for further processing, either on edge devices or in the cloud. Our goal in this doctoral research is to design and implement an adaptive data-driven ECC environment which combines mechanisms for optimal service placement and enables continuous data delivery from IoT devices to the appropriate services. Finally, we aim to evaluate and verify the solution through a real-world use case to demonstrate that the solution responds efficiently to dynamic changes in the ECC, including node, service, and network failures, while preserving high QoS for IoT devices.

Internet of Things ; Edge Computing ; Service Orchestration ; Data Streaming

nije evidentirano