research
∙
08/22/2023
Karasu: A Collaborative Approach to Efficient Cluster Configuration for Big Data Analytics
Selecting the right resources for big data analytics jobs is hard becaus...
share
research
∙
07/26/2023
Evaluation of Data Enrichment Methods for Distributed Stream Processing Systems
Stream processing has become a critical component in the architecture of...
research
∙
06/06/2023
Selecting Efficient Cluster Resources for Data Analytics: When and How to Allocate for In-Memory Processing?
Distributed dataflow systems such as Apache Spark or Apache Flink enable...
research
∙
01/25/2023
PULL: Reactive Log Anomaly Detection Based On Iterative PU Learning
Due to the complexity of modern IT services, failures can be manifold, o...
research
∙
11/24/2022
Probabilistic Time Series Forecasting for Adaptive Monitoring in Edge Computing Environments
With increasingly more computation being shifted to the edge of the netw...
research
∙
11/15/2022
Perona: Robust Infrastructure Fingerprinting for Resource-Efficient Big Data Analytics
Choosing a good resource configuration for big data analytics applicatio...
research
∙
11/08/2022
Ruya: Memory-Aware Iterative Optimization of Cluster Configurations for Big Data Processing
Selecting appropriate computational resources for data processing jobs o...
research
∙
08/16/2022
Reshi: Recommending Resources for Scientific Workflow Tasks on Heterogeneous Infrastructures
Scientific workflows typically comprise a multitude of different process...
research
∙
07/19/2022
Magpie: Automatically Tuning Static Parameters for Distributed File Systems using Deep Reinforcement Learning
Distributed file systems are widely used nowadays, yet using their defau...
research
∙
06/28/2022
Get Your Memory Right: The Crispy Resource Allocation Assistant for Large-Scale Data Processing
Distributed dataflow systems like Apache Spark and Apache Hadoop enable ...
research
∙
06/20/2022
Phoebe: QoS-Aware Distributed Stream Processing through Anticipating Dynamic Workloads
Distributed Stream Processing systems have become an essential part of b...
research
∙
06/01/2022
Collaborative Cluster Configuration for Distributed Data-Parallel Processing: A Research Overview
Many organizations routinely analyze large datasets using systems for di...
research
∙
05/05/2022
Cucumber: Renewable-Aware Admission Control for Delay-Tolerant Cloud and Edge Workloads
The growing electricity demand of cloud and edge computing increases ope...
research
∙
03/10/2022
Efficient Runtime Profiling for Black-box Machine Learning Services on Sensor Streams
In highly distributed environments such as cloud, edge and fog computing...
research
∙
11/26/2021
A Taxonomy of Anomalies in Log Data
Log data anomaly detection is a core component in the area of artificial...
research
∙
11/16/2021
On the Potential of Execution Traces for Batch Processing Workload Optimization in Public Clouds
With the growing amount of data, data processing workloads and the manag...
research
∙
11/15/2021
Training Data Reduction for Performance Models of Data Analytics Jobs in the Cloud
Distributed dataflow systems like Apache Flink and Apache Spark simplify...
research
∙
11/02/2021
LogLAB: Attention-Based Labeling of Log Data Anomalies via Weak Supervision
With increasing scale and complexity of cloud operations, automated dete...
research
∙
10/25/2021
Let's Wait Awhile: How Temporal Workload Shifting Can Reduce Carbon Emissions in the Cloud
Depending on energy sources and demand, the carbon intensity of the publ...
research
∙
09/20/2021
A2Log: Attentive Augmented Log Anomaly Detection
Anomaly detection becomes increasingly important for the dependability a...
research
∙
09/06/2021
Khaos: Dynamically Optimizing Checkpointing for Dependable Distributed Stream Processing
Distributed Stream Processing systems are becoming an increasingly essen...
research
∙
08/27/2021
Enel: Context-Aware Dynamic Scaling of Distributed Dataflow Jobs using Graph Propagation
Distributed dataflow systems like Spark and Flink enable the use of clus...
research
∙
08/10/2021
Evaluation of Load Prediction Techniques for Distributed Stream Processing
Distributed Stream Processing (DSP) systems enable processing large stre...
research
∙
07/29/2021
Bellamy: Reusing Performance Models for Distributed Dataflow Jobs Across Contexts
Distributed dataflow systems enable the use of clusters for scalable dat...
research
∙
07/28/2021
C3O: Collaborative Cluster Configuration Optimization for Distributed Data Processing in Public Clouds
Distributed dataflow systems enable data-parallel processing of large da...
research
∙
03/09/2021
Learning Dependencies in Distributed Cloud Applications to Identify and Localize Anomalies
Operation and maintenance of large distributed cloud applications can qu...
research
∙
02/25/2021
