10 citations · 13 across the 7 of their papers we have counts for
7 papers
MAIZX: A Carbon-Aware Framework for Optimizing Cloud Computing Emissions
Federico Ruilova, Ernst Gunnar Gran, Sven-Arne Reinemo
Cloud computing drives innovation but also poses significant environmental challenges due to its high-energy consumption and carbon emissions. Data centers account for 2-4% of glob…
Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector
Aafan Ahmad Toor, Jia-Chun Lin, Ernst Gunnar Gran
The exponential growth in the usage of Internet of Things in daily life has caused immense increase in the generation of time series data. Smart homes is one such domain where bulk…
DistTune: Distributed Fine-Grained Adaptive Traffic Speed Prediction for Growing Transportation Networks
Ming-Chang Lee, Jia-Chun Lin, Ernst Gunnar Gran
Over the past decade, many approaches have been introduced for traffic speed prediction. However, providing fine-grained, accurate, time-efficient, and adaptive traffic speed predi…
SALAD: Self-Adaptive Lightweight Anomaly Detection for Real-time Recurrent Time Series
Ming-Chang Lee, Jia-Chun Lin, Ernst Gunnar Gran
Real-world time series data often present recurrent or repetitive patterns and it is often generated in real time, such as transportation passenger volume, network traffic, system…
How Far Should We Look Back to Achieve Effective Real-Time Time-Series Anomaly Detection?
Ming-Chang Lee, Jia-Chun Lin, Ernst Gunnar Gran
Anomaly detection is the process of identifying unexpected events or ab-normalities in data, and it has been applied in many different areas such as system monitoring, fraud detect…
Distributed Fine-Grained Traffic Speed Prediction for Large-Scale Transportation Networks based on Automatic LSTM Customization and Sharing
Ming-Chang Lee, Jia-Chun Lin, Ernst Gunnar Gran
Short-term traffic speed prediction has been an important research topic in the past decade, and many approaches have been introduced. However, providing fine-grained, accurate, an…
RePAD: Real-time Proactive Anomaly Detection for Time Series
Ming-Chang Lee, Jia-Chun Lin, Ernst Gunnar Gran
During the past decade, many anomaly detection approaches have been introduced in different fields such as network monitoring, fraud detection, and intrusion detection. However, th…