Record link: 
http://hdl.handle.net/20.500.12708/215608
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Title: 
STORELESS: Serverless Workflow Scheduling with Federated Storage in Sky Computing
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Citation: 
Ristov, S., Hautz, M., Gritsch, P., Nastic, S., Prodan, R., & Felderer, M. (2025). STORELESS: Serverless Workflow Scheduling with Federated Storage in Sky Computing. In W. Gaaloul, M. Sheng, Q. Yu, & S. Yangui (Eds.), Service-Oriented Computing : 22nd International Conference, ICSOC 2024, Tunis, Tunisia, December 3–6, 2024, Proceedings, Part II (pp. 35–44). Springer Singapore. https://doi.org/10.1007/978-981-96-0808-9_3
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Publisher DOI: 
10.1007/978-981-96-0808-9_3
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Publication Type: 
Inproceedings - Full-Paper Contribution
en
Language: 
English
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Authors: 
Ristov, Sashko 
Hautz, Mika 
Gritsch, Philipp 
Nastic, Stefan 
Prodan, Radu 
Felderer, Michael 
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Organisational Unit: 
E194-02 - Forschungsbereich Distributed Systems 
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Published in: 
Service-Oriented Computing : 22nd International Conference, ICSOC 2024, Tunis, Tunisia, December 3–6, 2024, Proceedings, Part II 
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ISBN: 
978-981-96-0808-9
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Volume: 
15405
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DOI of the book: 
10.1007/978-981-96-0808-9
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Date (published): 
2025
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Event name: 
22nd International Conference on Service-Oriented Computing (ICSOC 2024) 
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Event date: 
3-Dec-2024 - 6-Dec-2024
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Event place: 
Tunis, Tunisia
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Number of Pages: 
10
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Publisher: 
Springer Singapore
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Peer reviewed: 
Yes
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Keywords: 
Federation; Scheduling; Serverless workflows; Storage
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Abstract: 
We observe irregular data transfer performance across federated serverless infrastructures (sometimes faster across providers than colocated), making the entire workflow scheduling even more challenging in federated FaaS and sky computing. This paper introduces StoreLess  – a novel workflow scheduler and heuristic algorithm for serverless storage attachments that dynamically selects, provisions, and configures suitable function deployments and storage backends from the federated serverless infrastructure. StoreLess improves workflow execution time by up to 30% by running cross-regional setup compared to the state-of-the-art.
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Project title: 
Rapid Recovery and Control of Urban Traffic During Accident Situations Based on Artificial Intelligence: 903884 (FFG - Österr. Forschungsförderungs- gesellschaft mbH) 
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Project (external): 
Land Tirol, Austria
KDT JU
Horizon Europe program
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Project ID: 
Grant F.35499
grant agreement 101140216, MATISSE
grant agreement 101093202, Graph-Massivizer
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Research Areas: 
Information Systems Engineering: 100%
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Science Branch: 
1020 - Informatik: 100%
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Appears in Collections:
Conference Paper

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