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20232026
most citedThe Common Workflow Scheduler Interface: Status Quo and Future Plans

2 citations · 4 across the 5 of their papers we have counts for

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cs.DC2026

From Sensors to Insight: Rapid, Edge-to-Core Application Development for Sensor-Driven Applications

Komal Thareja, Anirban Mandal, Ewa Deelman

Scientists increasingly rely on sensor-based data, yet transforming raw streams into insights across the edge-to-cloud continuum remains difficult. Provisioning heterogeneous infra…

cs.DC2026

(POSTER) From Sensors to Insight: Rapid, Edge-to-Core Application Development for Sensor-Driven Applications

Komal Thareja, Anirban Mandal, Ewa Deelman

Scientists increasingly rely on sensor-based data; however transforming raw streams into insights across the edge-to-cloud continuum remains difficult due to the breadth of experti…

cs.DC2026

SWARM+: Scalable and Resilient Multi-Agent Consensus for Decentralized Data-Aware Workload Management

Komal Thareja, Krishnan Raghavan, Hamza Safri +2

Distributed scientific workflows are increasingly executed across heterogeneous and geo-distributed computing environments, where centralized workload orchestration becomes a scala…

cs.DC2024★ 2 cited

Scaling on Frontier: Uncertainty Quantification Workflow Applications using ExaWorks to Enable Full System Utilization

Mikhail Titov, Robert Carson, Matthew Rolchigo +6

When running at scale, modern scientific workflows require middleware to handle allocated resources, distribute computing payloads and guarantee a resilient execution. While indivi…

cs.DC2023★ 2 cited

The Common Workflow Scheduler Interface: Status Quo and Future Plans

Fabian Lehmann, Jonathan Bader, Lauritz Thamsen +1

Nowadays, many scientific workflows from different domains, such as Remote Sensing, Astronomy, and Bioinformatics, are executed on large computing infrastructures managed by resour…