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Talks and Poster Presentations (with Proceedings-Entry):

V. Scoca, A. Aral, I. Brandic, R. de Nicola, R. B. Uriarte:
"Scheduling Latency-Sensitive Applications in Edge Computing";
Talk: 8th International Conference on Cloud Computing and Services Science, Funchal, Madeira, Portugal; 2019-03-19 - 2019-03-21; in: "Proceedings of the 8th International Conference on Cloud Computing and Services Science", (2018), ISBN: 978-989-758-295-0; 158 - 168.



English abstract:
Edge computing is an emerging technology that aims to include latency-sensitive and data-intensive applications such as mobile or IoT services, into the cloud ecosystem by placing computational resources at the edge of the network. Close proximity to producers and consumers of data brings significant benefits in latency and bandwidth. However, edge resources are, by definition, limited in comparison to cloud counterparts, thus, a trade-off exists between deploying a service closest to its users and avoiding resource overload. We propose a score-based edge service scheduling algorithm that evaluates both network and computational capabilities of edge nodes and outputs the maximum scoring mapping between services and resources. Our extensive simulation based on a live video streaming service, demonstrates significant improvements in both network delay and service time. Additionally, we compare edge computing technology with the state-of-the-art cloud computing and content delivery network solutions within the context of latency-sensitive and data-intensive applications. Our results show that edge computing enhanced with suggested scheduling algorithm is a viable solution for achieving high quality of service and responsivity in deploying such applications.

Keywords:
Edge Computing, Scheduling, Latency-Sensitive Services, Live Video Streaming, Resource Selection


"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
http://dx.doi.org/10.5220/0006706201580168

Electronic version of the publication:
https://publik.tuwien.ac.at/files/publik_270188.pdf


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