109 citations · 463 across the 69 of their papers we have counts for
11 papers · 1 filter
Simultaneous Genetic Evolution of Neural Networks for Optimal SFC Embedding
Theviyanthan Krishnamohan, Lauritz Thamsen, Paul Harvey
The reliance of organisations on computer networks is enabled by network programmability, which is typically achieved through Service Function Chaining. These chains virtualise net…
Spatio-Temporal Shifting to Reduce Carbon, Water, and Land-Use Footprints of Cloud Workloads
Giulio Attenni, Youssef Moawad, Novella Bartolini +1
In this paper, we investigate the potential of spatial and temporal cloud workload shifting to reduce carbon, water, and land use footprints. Specifically, we perform a simulation…
HyProv: Hybrid Provenance Management for Scientific Workflows
Vasilis Bountris, Lauritz Thamsen, Ulf Leser
Provenance plays a crucial role in scientific workflow execution, for instance by providing data for failure analysis, real-time monitoring, or statistics on resource utilization f…
BENNS: A Surrogate Model for Hybrid Online-Offline Evolution of SFC Embedding
Theviyanthan Krishnamohan, Lauritz Thamsen, Paul Harvey
Service Function Chains (SFCs) enable programmatic control of the functions and services in a computer network. By leveraging Software Defined Networking to control the links betwe…
A Systematic Evaluation of the Potential of Carbon-Aware Execution for Scientific Workflows
Kathleen West, Youssef Moawad, Fabian Lehmann +4
Scientific workflows are critical to scientific data analysis and often involve computationally intensive processing of large datasets on compute clusters. As such, their execution…
Energy-Aware Workflow Execution: An Overview of Techniques for Saving Energy and Emissions in Scientific Compute Clusters
Lauritz Thamsen, Yehia Elkhatib, Paul Harvey +3
Scientific research in many fields routinely requires the analysis of large datasets, and scientists often employ workflow systems to leverage clusters of computers for their data…
Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art
Jonathan Bader, Kathleen West, Soeren Becker +5
Scientific workflow management systems support large-scale data analysis on cluster infrastructures. For this, they interact with resource managers which schedule workflow tasks on…
WOW: Workflow-Aware Data Movement and Task Scheduling for Dynamic Scientific Workflows
Fabian Lehmann, Jonathan Bader, Friedrich Tschirpke +6
Scientific workflows process extensive data sets over clusters of independent nodes, which requires a complex stack of infrastructure components, especially a resource manager (RM)…
Exploring the Potential of Carbon-Aware Execution for Scientific Workflows
Kathleen West, Fabian Lehmann, Vasilis Bountris +3
Scientific workflows are widely used to automate scientific data analysis and often involve processing large quantities of data on compute clusters. As such, their execution tends…
Flora: Efficient Cloud Resource Selection for Big Data Processing via Job Classification
Jonathan Will, Lauritz Thamsen, Jonathan Bader +1
Distributed dataflow systems like Spark and Flink enable data-parallel processing of large datasets on clusters of cloud resources. Yet, selecting appropriate computational resourc…
Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling
Jonathan Will, Nico Treide, Lauritz Thamsen +1
Distributed dataflow systems like Spark and Flink enable data-parallel processing of large datasets on clusters. Yet, selecting appropriate computational resources for dataflow job…