61 citations · 319 across the 56 of their papers we have counts for
6 papers · 1 filter
Sponge: Inference Serving with Dynamic SLOs Using In-Place Vertical Scaling
Kamran Razavi, Saeid Ghafouri, Max Mühlhäuser +2
Mobile and IoT applications increasingly adopt deep learning inference to provide intelligence. Inference requests are typically sent to a cloud infrastructure over a wireless netw…
HEET: A Heterogeneity Measure to Quantify the Difference across Distributed Computing Systems
Ali Mokhtari, Saeid Ghafouri, Pooyan Jamshidi +1
Although system heterogeneity has been extensively studied in the past, there is yet to be a study on measuring the impact of heterogeneity on system performance. For this purpose,…
FELARE: Fair Scheduling of Machine Learning Tasks on Heterogeneous Edge Systems
Ali Mokhtari, Md Abir Hossen, Pooyan Jamshidi +1
Edge computing enables smart IoT-based systems via concurrent and continuous execution of latency-sensitive machine learning (ML) applications. These edge-based machine learning sy…
Kuksa*: Self-Adaptive Microservices in Automotive Systems
Ahmad Banijamali, Pasi Kuvaja, Markku Oivo +1
In pervasive dynamic environments, vehicles connect to other objects to send operational data and receive updates so that vehicular applications can provide services to users on de…
A Comparison of Reinforcement Learning Techniques for Fuzzy Cloud Auto-Scaling
Hamid Arabnejad, Claus Pahl, Pooyan Jamshidi +1
A goal of cloud service management is to design self-adaptable auto-scaler to react to workload fluctuations and changing the resources assigned. The key problem is how and when to…
An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing Systems
Pooyan Jamshidi, Giuliano Casale
Finding optimal configurations for Stream Processing Systems (SPS) is a challenging problem due to the large number of parameters that can influence their performance and the lack…