Call For Papers

Second International Workshop on Urgent Analytics for the Computing Continuum (QUICK'2024)
Co-located with the 24th IEEE/ACM International Symposium on Cluster, Cloud, and Internet Computing (CCGrid 2024)

----------------- Important Dates --------------------
Abstract Submission Deadline: Dec 15, 2023 AoE
Paper Submission Deadline: Dec 22, 2023 AoE
Author Notification: Feb 23, 2024
--------------------------------------------------------

Philadelphia, USA, | May 6, 2024
https://quick-workshop.github.io/

The Second Workshop on Urgent Analytics for Computing Continuum (QUICK'2024) provides a platform for distributed applications that enable important decision-making under time and quality constraints while maintaining desired confidence. We seek scientific contributions that leverage the aggregation of heterogeneous resources along the data path from the IoT/Edge to the Cloud and beyond, also known as the Computing Continuum, to support critical analytics applications. Data-driven dynamic workflows, which combine knowledge from multiple data sources and integrate it on-demand with distributed, large-scale computational models, have the potential to address today’s global grand challenges in science, engineering, and society.

We are looking for original high-quality research and position papers on urgent applications, services, and system software for the computing continuum.
Topics of interest for workshop submissions include (but are not limited to):

- Algorithms, models and systems considerations in designing urgent applications in the Computing Continuum
- Programming support for user expectations and constraints in terms of response time, solution quality, data resolution, cost, energy, etc.
- Run-time techniques to provide flexible execution models for computation and communication.
- Resource management frameworks and interfaces supporting scheduling, resource allocations and application execution for the computing continuum.
- Use of AI and ML techniques to steer urgency in systems and applications.
- Experiences and use cases applying urgent science to computing continuum infrastructures.
- Autonomic Computing in the Computing Continuum
- Feedback, Control and Observability across the Computing Continuum
- Distributed Machine Learning in the Computing Continuum
- Edge Intelligence models and architectures
- Policy driven service and resource life-cycle management