Standard
Autonomic resource provisioning for cloud-based software. / Jamshidi, Pooyan
; Ahmad, Aakash; Pahl, Claus.
9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014 - Proceedings. The Association for Computing Machinery, 2014. p. 95-104 (9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014 - Proceedings).
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
Jamshidi, P
, Ahmad, A & Pahl, C 2014,
Autonomic resource provisioning for cloud-based software. in
9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014 - Proceedings. 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014 - Proceedings, The Association for Computing Machinery, pp. 95-104, 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014, Hyderabad, India,
2/06/14.
https://doi.org/10.1145/2593929.2593940APA
Vancouver
Jamshidi P
, Ahmad A, Pahl C.
Autonomic resource provisioning for cloud-based software. In 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014 - Proceedings. The Association for Computing Machinery. 2014. p. 95-104. (9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014 - Proceedings). doi: 10.1145/2593929.2593940
Author
Jamshidi, Pooyan
; Ahmad, Aakash ; Pahl, Claus. /
Autonomic resource provisioning for cloud-based software. 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014 - Proceedings. The Association for Computing Machinery, 2014. pp. 95-104 (9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014 - Proceedings).
Bibtex
@inproceedings{985723c6efdd48c2a07b73044eea732d,
title = "Autonomic resource provisioning for cloud-based software",
abstract = "Cloud elasticity provides a software system with the ability to maintain optimal user experience by automatically acquiring and releasing resources, while paying only for what has been consumed. The mechanism for automatically adding or removing resources on the fly is referred to as auto-scaling. The state-of-thepractice with respect to auto-scaling involves specifying thresholdbased rules to implement elasticity policies for cloud-based applications. However, there are several shortcomings regarding this approach. Firstly, the elasticity rules must be specified precisely by quantitative values, which requires deep knowledge and expertise. Furthermore, existing approaches do not explicitly deal with uncertainty in cloud-based software, where noise and unexpected events are common. This paper exploits fuzzy logic to enable qualitative specification of elasticity rules for cloud-based software. In addition, this paper discusses a control theoretical approach using type-2 fuzzy logic systems to reason about elasticity under uncertainties. We conduct several experiments to demonstrate that cloud-based software enhanced with such elasticity controller can robustly handle unexpected spikes in the workload and provide acceptable user experience. This translates into increased profit for the cloud application owner.",
keywords = "Auto-scaling, Cloud computing, Elasticity, Uncertainty",
author = "Pooyan Jamshidi and Aakash Ahmad and Claus Pahl",
year = "2014",
month = jun,
day = "2",
doi = "10.1145/2593929.2593940",
language = "English",
isbn = "9781450328647",
series = "9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014 - Proceedings",
publisher = "The Association for Computing Machinery",
pages = "95--104",
booktitle = "9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014 - Proceedings",
note = "9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014 ; Conference date: 02-06-2014 Through 03-06-2014",
}
RIS
TY - GEN
T1 - Autonomic resource provisioning for cloud-based software
AU - Jamshidi, Pooyan
AU - Ahmad, Aakash
AU - Pahl, Claus
PY - 2014/6/2
Y1 - 2014/6/2
N2 - Cloud elasticity provides a software system with the ability to maintain optimal user experience by automatically acquiring and releasing resources, while paying only for what has been consumed. The mechanism for automatically adding or removing resources on the fly is referred to as auto-scaling. The state-of-thepractice with respect to auto-scaling involves specifying thresholdbased rules to implement elasticity policies for cloud-based applications. However, there are several shortcomings regarding this approach. Firstly, the elasticity rules must be specified precisely by quantitative values, which requires deep knowledge and expertise. Furthermore, existing approaches do not explicitly deal with uncertainty in cloud-based software, where noise and unexpected events are common. This paper exploits fuzzy logic to enable qualitative specification of elasticity rules for cloud-based software. In addition, this paper discusses a control theoretical approach using type-2 fuzzy logic systems to reason about elasticity under uncertainties. We conduct several experiments to demonstrate that cloud-based software enhanced with such elasticity controller can robustly handle unexpected spikes in the workload and provide acceptable user experience. This translates into increased profit for the cloud application owner.
AB - Cloud elasticity provides a software system with the ability to maintain optimal user experience by automatically acquiring and releasing resources, while paying only for what has been consumed. The mechanism for automatically adding or removing resources on the fly is referred to as auto-scaling. The state-of-thepractice with respect to auto-scaling involves specifying thresholdbased rules to implement elasticity policies for cloud-based applications. However, there are several shortcomings regarding this approach. Firstly, the elasticity rules must be specified precisely by quantitative values, which requires deep knowledge and expertise. Furthermore, existing approaches do not explicitly deal with uncertainty in cloud-based software, where noise and unexpected events are common. This paper exploits fuzzy logic to enable qualitative specification of elasticity rules for cloud-based software. In addition, this paper discusses a control theoretical approach using type-2 fuzzy logic systems to reason about elasticity under uncertainties. We conduct several experiments to demonstrate that cloud-based software enhanced with such elasticity controller can robustly handle unexpected spikes in the workload and provide acceptable user experience. This translates into increased profit for the cloud application owner.
KW - Auto-scaling
KW - Cloud computing
KW - Elasticity
KW - Uncertainty
U2 - 10.1145/2593929.2593940
DO - 10.1145/2593929.2593940
M3 - Conference contribution/Paper
AN - SCOPUS:84903737232
SN - 9781450328647
T3 - 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014 - Proceedings
SP - 95
EP - 104
BT - 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014 - Proceedings
PB - The Association for Computing Machinery
T2 - 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014
Y2 - 2 June 2014 through 3 June 2014
ER -
