Supporting Cloud IaaS Users in Detecting Performance-based Violation for Streaming Applications

Esha Barlaskar; Kiril Dichev; Peter Kilpatrick; Ivor Spence; Dimitrios S. Nikolopoulos

doi:10.1109/ICAC.2018.00027

Supporting Cloud IaaS Users in Detecting Performance-based Violation for Streaming Applications

Esha Barlaskar, Kiril Dichev, Peter Kilpatrick, Ivor Spence, Dimitrios S. Nikolopoulos

School of Electronics, Electrical Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

Cloud infrastructure-as-a-service (IaaS) users require stable performance for their applications so that the Quality of Service (QoS) constraints are satisfied. However, they generally experience performance variability, primarily due to multi-tenancy. Such variability may lead to QoS violations for the deployed applications. Existing cloud infrastructure solutions offered by cloud providers (CPs) do not have facilities to detect such violations. Hence, cloud users need to take responsibility for monitoring the performance of their applications in order to detect application-specific QoS violations. In this paper, we propose a novel algorithm for detecting QoS violation for media streaming applications. The algorithm compares the cumulative value of the expected streamed data against the cumulative value of the measured streamed data. Based on this comparison, the algorithm may raise QoS violation alarms. We evaluate the algorithm by deploying a media streaming application in a lab-based cloud setup. Experimental results demonstrate the correctness of the proposed algorithm.

Original language	English
Title of host publication	2018 IEEE International Conference on Autonomic Computing (ICAC)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	163-168
Number of pages	6
DOIs	https://doi.org/10.1109/ICAC.2018.00027
Publication status	Published - 22 Oct 2018
Event	15th IEEE International Conference on Autonomic Computing (ICAC) - Trento, Italy Duration: 03 Sep 2018 → 07 Sep 2018

Publication series

Name	2018 IEEE International Conference on Autonomic Computing (ICAC)
Publisher	IEEE
ISSN (Electronic)	2474-0756

Conference

Conference	15th IEEE International Conference on Autonomic Computing (ICAC)
Country/Territory	Italy
City	Trento
Period	03/09/2018 → 07/09/2018

Keywords

Cloud Computing,
Cloud Monitoring
QoS Vi- olation Detection
Media Streaming Application

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10.1109/ICAC.2018.00027Licence: Unspecified

Supporting Cloud IaaS Users in Detecting Performance-based Violation for Streaming Applications
© 2018 IEEE. This work is made available online in accordance with the publisher’s policies. Please refer to any applicable terms of use of the publisher.
Accepted author manuscript, 379 KBLicence: Unspecified

User-centric cloud application management
Author: Barlaskar, E., Dec 2020
Supervisor: Spence, I. (Supervisor), Kilpatrick, P. (Supervisor) & Nikolopoulos, D. (Supervisor)
Student thesis: Doctoral Thesis › Doctor of Philosophy

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Cite this

Barlaskar, E., Dichev, K., Kilpatrick, P., Spence, I., & Nikolopoulos, D. S. (2018). Supporting Cloud IaaS Users in Detecting Performance-based Violation for Streaming Applications. In 2018 IEEE International Conference on Autonomic Computing (ICAC) (pp. 163-168). (2018 IEEE International Conference on Autonomic Computing (ICAC)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICAC.2018.00027

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title = "Supporting Cloud IaaS Users in Detecting Performance-based Violation for Streaming Applications",

abstract = "Cloud infrastructure-as-a-service (IaaS) users require stable performance for their applications so that the Quality of Service (QoS) constraints are satisfied. However, they generally experience performance variability, primarily due to multi-tenancy. Such variability may lead to QoS violations for the deployed applications. Existing cloud infrastructure solutions offered by cloud providers (CPs) do not have facilities to detect such violations. Hence, cloud users need to take responsibility for monitoring the performance of their applications in order to detect application-specific QoS violations. In this paper, we propose a novel algorithm for detecting QoS violation for media streaming applications. The algorithm compares the cumulative value of the expected streamed data against the cumulative value of the measured streamed data. Based on this comparison, the algorithm may raise QoS violation alarms. We evaluate the algorithm by deploying a media streaming application in a lab-based cloud setup. Experimental results demonstrate the correctness of the proposed algorithm.",

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Barlaskar, E, Dichev, K, Kilpatrick, P , Spence, I & Nikolopoulos, DS 2018, Supporting Cloud IaaS Users in Detecting Performance-based Violation for Streaming Applications. in 2018 IEEE International Conference on Autonomic Computing (ICAC). 2018 IEEE International Conference on Autonomic Computing (ICAC), Institute of Electrical and Electronics Engineers Inc., pp. 163-168, 15th IEEE International Conference on Autonomic Computing (ICAC), Trento, Italy, 03/09/2018. https://doi.org/10.1109/ICAC.2018.00027

Supporting Cloud IaaS Users in Detecting Performance-based Violation for Streaming Applications. / Barlaskar, Esha; Dichev, Kiril; Kilpatrick, Peter et al.

2018 IEEE International Conference on Autonomic Computing (ICAC). Institute of Electrical and Electronics Engineers Inc., 2018. p. 163-168 (2018 IEEE International Conference on Autonomic Computing (ICAC)).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Supporting Cloud IaaS Users in Detecting Performance-based Violation for Streaming Applications

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AU - Dichev, Kiril

AU - Kilpatrick, Peter

AU - Spence, Ivor

AU - Nikolopoulos, Dimitrios S.

PY - 2018/10/22

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AB - Cloud infrastructure-as-a-service (IaaS) users require stable performance for their applications so that the Quality of Service (QoS) constraints are satisfied. However, they generally experience performance variability, primarily due to multi-tenancy. Such variability may lead to QoS violations for the deployed applications. Existing cloud infrastructure solutions offered by cloud providers (CPs) do not have facilities to detect such violations. Hence, cloud users need to take responsibility for monitoring the performance of their applications in order to detect application-specific QoS violations. In this paper, we propose a novel algorithm for detecting QoS violation for media streaming applications. The algorithm compares the cumulative value of the expected streamed data against the cumulative value of the measured streamed data. Based on this comparison, the algorithm may raise QoS violation alarms. We evaluate the algorithm by deploying a media streaming application in a lab-based cloud setup. Experimental results demonstrate the correctness of the proposed algorithm.

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Barlaskar E, Dichev K, Kilpatrick P , Spence I, Nikolopoulos DS. Supporting Cloud IaaS Users in Detecting Performance-based Violation for Streaming Applications. In 2018 IEEE International Conference on Autonomic Computing (ICAC). Institute of Electrical and Electronics Engineers Inc. 2018. p. 163-168. (2018 IEEE International Conference on Autonomic Computing (ICAC)). doi: 10.1109/ICAC.2018.00027

Supporting Cloud IaaS Users in Detecting Performance-based Violation for Streaming Applications

Abstract

Publication series

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Keywords

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Student theses

User-centric cloud application management

Cite this