Daniel Balouek-Thomert

AI Techniques in the Microservices Life-Cycle: A Systematic Mapping Study

The use of AI in microservices (MSs) is an emerging field as indicated by a substantial number of surveys. However these surveys focus on a specific problem using specific AI techniques, therefore...

Edge Based Data-Driven Pipelines (Technical Report)

This research reports investigates an edge on-device stream processing platform, which extends the serverless com- puting model to the edge to help facilitate real-time data analytics across the...

An Edge-Based Framework for Enabling Data-Driven Pipelines for IoT Systems

Energy-Aware Server Provisioning by Introducing Middleware-Level Dynamic Green Scheduling

Pulsar: Enabling Dynamic Data-Driven IoT Applications

Online Decision-Making Using Edge Resources for Content-Driven Stream Processing

Supporting Data-Driven Workflows Enabled by Large Scale Observatories

Distributed Operator Placement for IoT Data Analytics Across Edge and Cloud Resources

Trading Data Size and CNN Confidence Score for Energy Efficient CPS Node Communications

Enhancing microservices architectures using data-driven service discovery and QoS guarantees

Enabling microservices management for Deep Learning applications across the Edge-Cloud Continuum

Runtime Management of Data Quality for Scientific Observatories Using Edge and In-Transit Resources

Leveraging energy-efficient non-lossy compression for data-intensive applications

MDSC: modelling distributed stream processing across the edge-to-cloud continuum

Ensemble-Based Network Edge Processing

TEMA: Event Driven Serverless Workflows Platform for Natural Disaster Management

Evaluating policy-driven adaptation on the Edge-to-Cloud Continuum

Edge Enhanced Deep Learning System for Large-Scale Video Stream Analytics