Predicting the Stability of Large-scale Distributed Stream Processing Systems on the Cloud

Tri Minh Truong; Aaron Harwood; Richard O. Sinnott

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Paper

Predicting the Stability of Large-scale Distributed Stream Processing Systems on the Cloud

Topics: Cloud Application Scalability and Availability; Cloud Applications Performance and Monitoring; QoS for Applications on Clouds; Resource Management

In Proceedings of the 7th International Conference on Cloud Computing and Services Science CLOSER - Volume 1, 603-610, 2017 , Porto, Portugal

Authors: Tri Minh Truong ; Aaron Harwood and Richard O. Sinnott

Affiliation: University of Melbourne, Australia

Keyword(s): Stability, Resource Estimates, Stream Processing Systems.

Abstract: Large-scale topology-based stream processing systems are non-trivial to build and deploy. They require understanding of the performance, cost of deployment and considerations of potential downtime. Our work considers stability as a primary characteristic of these systems. By stability, we mean that unstable systems exhibit large-spikes in latency and can drop throughput frequently or unpredictably. Such instabilities can be due to variations of workloads or underlying hardware platforms that are often difficult to predict. To understand and tackle this for large-scale stream processing systems, we apply queueing theory and simulate the results through a series of experiments on the Cloud.

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Paper citation in several formats:

Truong, T.; Harwood, A. and Sinnott, R. (2017). Predicting the Stability of Large-scale Distributed Stream Processing Systems on the Cloud. In Proceedings of the 7th International Conference on Cloud Computing and Services Science - CLOSER; ISBN 978-989-758-243-1; ISSN 2184-5042, SciTePress, pages 603-610. DOI: 10.5220/0006357606030610

@conference{closer17,
author={Tri Minh Truong. and Aaron Harwood. and Richard O. Sinnott.},
title={Predicting the Stability of Large-scale Distributed Stream Processing Systems on the Cloud},
booktitle={Proceedings of the 7th International Conference on Cloud Computing and Services Science - CLOSER},
year={2017},
pages={603-610},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006357606030610},
isbn={978-989-758-243-1},
issn={2184-5042},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Cloud Computing and Services Science - CLOSER
TI - Predicting the Stability of Large-scale Distributed Stream Processing Systems on the Cloud
SN - 978-989-758-243-1
IS - 2184-5042
AU - Truong, T.
AU - Harwood, A.
AU - Sinnott, R.
PY - 2017
SP - 603
EP - 610
DO - 10.5220/0006357606030610
PB - SciTePress