Run-time adaptation of stream processing spanning the cloud and the edge-Reference-Cited by-同舟云学术

Run-time adaptation of stream processing spanning the cloud and the edge

Published:2021-12-06 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion
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Author:

Cattermole Adam¹,Dowland Jonathan²,Watson Paul¹

Affiliation:

1. Newcastle University, UK

2. Red Hat, Inc., UK

Funder

Engineering and Physical Sciences Research Council

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3492323.3495627

Reference24 articles.

1. Apache flink: Stream and batch processing in a single engine;Carbone Paris;Bulletin of the IEEE Computer Society Technical Committee on Data Engineering,2015

2. Decentralized self-adaptation for elastic Data Stream Processing

3. Adaptive Scheduling Parallel Jobs with Dynamic Batching in Spark Streaming

4. Adaptive Stream Processing using Dynamic Batch Sizing

5. Recent Advancements in Event Processing

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1. A Self-Distributing System Framework for the Computing Continuum;2023 32nd International Conference on Computer Communications and Networks (ICCCN);2023-07

2. Logical Optimisation and Cost Modelling of Stream-Processing Programs Written in a Purely-Functional Framework;2022 IEEE/ACM 15th International Conference on Utility and Cloud Computing (UCC);2022-12

3. Exploiting the Potential of the Edge-Cloud Continuum with Self-distributing Systems;2022 IEEE/ACM 15th International Conference on Utility and Cloud Computing (UCC);2022-12