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Cloud-based data stream processing

Cloud-based data stream processing
Cloud-based data stream processing

In this tutorial we present the results of recent research about the cloud enablement of data streaming systems. We illustrate, based on both industrial as well as academic prototypes, new emerging uses cases and research trends. Specifically, we focus on novel approaches for (1) scalability and (2) fault tolerance in large scale distributed streaming systems. In general, new fault tolerance mechanisms strive to be more robust and at the same time introduce less overhead. Novel load balancing approaches focus on elastic scaling over hundreds of instances based on the data and query workload. Finally, we present open challenges for the next generation of cloud-based data stream processing engines.

cloud-based data stream processing, fault tolerance, load balancing
238-245
ACM Press
Heinze, Thomas
cb743278-0f86-403d-b9ce-863d0bc354a1
Aniello, Leonardo
9846e2e4-1303-4b8b-9092-5d8e9bb514c3
Querzoni, Leonardo
c0eee656-74e7-419d-876c-3cad808683d6
Jerzak, Zbigniew
a03cdb3d-7057-4c51-8bd5-7e5fa7c165d3
Heinze, Thomas
cb743278-0f86-403d-b9ce-863d0bc354a1
Aniello, Leonardo
9846e2e4-1303-4b8b-9092-5d8e9bb514c3
Querzoni, Leonardo
c0eee656-74e7-419d-876c-3cad808683d6
Jerzak, Zbigniew
a03cdb3d-7057-4c51-8bd5-7e5fa7c165d3

Heinze, Thomas, Aniello, Leonardo, Querzoni, Leonardo and Jerzak, Zbigniew (2014) Cloud-based data stream processing. In DEBS 2014 - Proceedings of the 8th ACM International Conference on Distributed Event-Based Systems. ACM Press. pp. 238-245 . (doi:10.1145/2611286.2611309).

Record type: Conference or Workshop Item (Paper)

Abstract

In this tutorial we present the results of recent research about the cloud enablement of data streaming systems. We illustrate, based on both industrial as well as academic prototypes, new emerging uses cases and research trends. Specifically, we focus on novel approaches for (1) scalability and (2) fault tolerance in large scale distributed streaming systems. In general, new fault tolerance mechanisms strive to be more robust and at the same time introduce less overhead. Novel load balancing approaches focus on elastic scaling over hundreds of instances based on the data and query workload. Finally, we present open challenges for the next generation of cloud-based data stream processing engines.

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Tutorial: Cloud-based Data Stream Processing - Accepted Manuscript
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More information

Accepted/In Press date: 1 February 2014
Published date: 2014
Additional Information: Copyright: Copyright 2014 Elsevier B.V., All rights reserved.
Venue - Dates: 8th ACM International Conference on Distributed Event-Based Systems, DEBS 2014, , Mumbai, India, 2014-05-26 - 2014-05-29
Keywords: cloud-based data stream processing, fault tolerance, load balancing

Identifiers

Local EPrints ID: 419693
URI: http://eprints.soton.ac.uk/id/eprint/419693
PURE UUID: 6c343183-30b4-4d9f-b8ee-4b9d7c6b3bb4
ORCID for Leonardo Aniello: ORCID iD orcid.org/0000-0003-2886-8445

Catalogue record

Date deposited: 19 Apr 2018 16:30
Last modified: 29 Jul 2022 02:01

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Contributors

Author: Thomas Heinze
Author: Leonardo Aniello ORCID iD
Author: Leonardo Querzoni
Author: Zbigniew Jerzak

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