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Talks and Poster Presentations (with Proceedings-Entry):

S. Nastic, T. Pusztai, A. Morichetta, V. Casamayor Pujol, S. Dustdar, D. Vij, Y. Xiong:
"Polaris Scheduler: Edge Sensitive and SLO Aware Workload Scheduling in Cloud-Edge-IoT Clusters";
Talk: IEEE 14th International Conference on Cloud Computing (CLOUD 2021) - Online Conference, Chicago, IL, USA (invited); 2021-09-05 - 2021-09-11; in: "Proceedings of the IEEE 14th International Conference on Cloud Computing (CLOUD 2021)", C. Ardagna, C. Chang, E. Damiani, R. Ranjan, Z. Wang, R. Ward, J. Zhang, W. Zhang (ed.); IEEE, (2021), ISBN: 978-1-6654-0061-9; 206 - 216.



English abstract:
Application workload scheduling in hybrid Cloud-Edge-IoT infrastructures has been extensively researched over the last years. The recent trend of containerizing application workloads, both in the cloud and on the edge, has further fueled the need for more advanced scheduling solutions in these hybrid infrastructures. Unfortunately, most of the current approaches are not fully sensitive to the edge properties and also lack adequate support for Service Level Objective (SLO) awareness. Previously, we introduced software defined gateways (SDGs), which enable managing novel edge resources at scale. At the same time Kubernetes was initially released. In spite of not being specifically developed for the edge, Kubernetes implements many of the design principles introduced by our SDGs, making it suitable for building SDG extensions on top of it. In this paper we present Polaris Scheduler - a novel scheduling framework, which enables edge sensitive and SLO aware scheduling in the Cloud-Edge-IoT Continuum. Polaris Scheduler is being developed as a part of Linux Foundation's Centaurus project. We discuss the main research challenges, the approach, and the vision of SLO aware edge sensitive scheduling.

Keywords:
Edge Computing, Service Level Objectives, Elasticity, Container Scheduling


"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
http://dx.doi.org/10.1109/CLOUD53861.2021.00034


Created from the Publication Database of the Vienna University of Technology.