Jonathan Will

Orcid: 0009-0005-7834-8845

According to our database1, Jonathan Will authored at least 19 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Sizey: Memory-Efficient Execution of Scientific Workflow Tasks.
CoRR, 2024

Privacy-Preserving Sharing of Data Analytics Runtime Metrics for Performance Modeling.
Proceedings of the Companion of the 15th ACM/SPEC International Conference on Performance Engineering, 2024

2023
Karasu: A Collaborative Approach to Efficient Cluster Configuration for Big Data Analytics.
CoRR, 2023

Selecting Efficient Cluster Resources for Data Analytics: When and How to Allocate for In-Memory Processing?
Proceedings of the 35th International Conference on Scientific and Statistical Database Management, 2023

Towards a Peer-to-Peer Data Distribution Layer for Efficient and Collaborative Resource Optimization of Distributed Dataflow Applications.
Proceedings of the IEEE International Conference on Big Data, 2023

2022
Collaborative Cluster Configuration for Distributed Data-Parallel Processing: A Research Overview.
Datenbank-Spektrum, 2022

Lotaru: Locally Estimating Runtimes of Scientific Workflow Tasks in Heterogeneous Clusters.
Proceedings of the SSDBM 2022: 34th International Conference on Scientific and Statistical Database Management, Copenhagen, Denmark, July 6, 2022

Reshi: Recommending Resources for Scientific Workflow Tasks on Heterogeneous Infrastructures.
Proceedings of the IEEE International Performance, 2022

Get Your Memory Right: The Crispy Resource Allocation Assistant for Large-Scale Data Processing.
Proceedings of the IEEE International Conference on Cloud Engineering, 2022

Ruya: Memory-Aware Iterative Optimization of Cluster Configurations for Big Data Processing.
Proceedings of the IEEE International Conference on Big Data, 2022

Perona: Robust Infrastructure Fingerprinting for Resource-Efficient Big Data Analytics.
Proceedings of the IEEE International Conference on Big Data, 2022

2021
Enel: Context-Aware Dynamic Scaling of Distributed Dataflow Jobs using Graph Propagation.
Proceedings of the IEEE International Performance, 2021

C3O: Collaborative Cluster Configuration Optimization for Distributed Data Processing in Public Clouds.
Proceedings of the IEEE International Conference on Cloud Engineering, 2021

Dependable IoT Data Stream Processing for Monitoring and Control of Urban Infrastructures.
Proceedings of the IEEE International Conference on Cloud Engineering, 2021

Bellamy: Reusing Performance Models for Distributed Dataflow Jobs Across Contexts.
Proceedings of the IEEE International Conference on Cluster Computing, 2021

Training Data Reduction for Performance Models of Data Analytics Jobs in the Cloud.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

On the Potential of Execution Traces for Batch Processing Workload Optimization in Public Clouds.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Tarema: Adaptive Resource Allocation for Scalable Scientific Workflows in Heterogeneous Clusters.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020
Towards Collaborative Optimization of Cluster Configurations for Distributed Dataflow Jobs.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020


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