Managing dynamic enterprise and urgent workloads on clouds using layered queuing and historical performance models

Research output: Contribution to journalArticlepeer-review

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Managing dynamic enterprise and urgent workloads on clouds using layered queuing and historical performance models. / Bacigalupo, David A.; Van Hemert, Jano; Chen, Xiaoyu; Usmani, Asif; Chester, Adam P.; He, Ligang; Dillenberger, Donna N.; Wills, Gary B.; Gilbert, Lester; Jarvis, Stephen A.

In: Simulation Modelling Practice and Theory, Vol. 19, No. 6, 06.2011, p. 1479-1495.

Research output: Contribution to journalArticlepeer-review

Harvard

Bacigalupo, DA, Van Hemert, J, Chen, X, Usmani, A, Chester, AP, He, L, Dillenberger, DN, Wills, GB, Gilbert, L & Jarvis, SA 2011, 'Managing dynamic enterprise and urgent workloads on clouds using layered queuing and historical performance models', Simulation Modelling Practice and Theory, vol. 19, no. 6, pp. 1479-1495. https://doi.org/10.1016/j.simpat.2011.01.007

APA

Bacigalupo, D. A., Van Hemert, J., Chen, X., Usmani, A., Chester, A. P., He, L., Dillenberger, D. N., Wills, G. B., Gilbert, L., & Jarvis, S. A. (2011). Managing dynamic enterprise and urgent workloads on clouds using layered queuing and historical performance models. Simulation Modelling Practice and Theory, 19(6), 1479-1495. https://doi.org/10.1016/j.simpat.2011.01.007

Vancouver

Author

Bacigalupo, David A. ; Van Hemert, Jano ; Chen, Xiaoyu ; Usmani, Asif ; Chester, Adam P. ; He, Ligang ; Dillenberger, Donna N. ; Wills, Gary B. ; Gilbert, Lester ; Jarvis, Stephen A. / Managing dynamic enterprise and urgent workloads on clouds using layered queuing and historical performance models. In: Simulation Modelling Practice and Theory. 2011 ; Vol. 19, No. 6. pp. 1479-1495.

Bibtex

@article{9a8df48191974e699f8c205ee0ed254d,
title = "Managing dynamic enterprise and urgent workloads on clouds using layered queuing and historical performance models",
abstract = "The automatic allocation of enterprise workload to resources can be enhanced by being able to make what-if response time predictions whilst different allocations are being considered. We experimentally investigate an historical and a layered queuing performance model and show how they can provide a good level of support for a dynamic-urgent cloud environment. Using this we define, implement and experimentally investigate the effectiveness of a prediction-based cloud workload and resource management algorithm. Based on these experimental analyses we: (i) comparatively evaluate the layered queuing and historical techniques; (ii) evaluate the effectiveness of the management algorithm in different operating scenarios; and (iii) provide guidance on using prediction-based workload and resource management.",
keywords = "Cloud, FireGrid, HYDRA historical model, Layered queuing, Performance modelling",
author = "Bacigalupo, {David A.} and {Van Hemert}, Jano and Xiaoyu Chen and Asif Usmani and Chester, {Adam P.} and Ligang He and Dillenberger, {Donna N.} and Wills, {Gary B.} and Lester Gilbert and Jarvis, {Stephen A.}",
note = "Funding Information: This work was sponsored in part by the JISC TeciRes project, the Technology Strategy Board FireGrid Project, The University of Edinburgh School of Informatics, the EPSRC DOPCHE Project (GR/S03058/01). We gratefully acknowledge the assistance during current and earlier versions of this work of: M. Atkinson, G. Beckett, J. Koetsier, S. Koo, T. Liu, I. Mitrani, A. van Moorsel, G. Nudd, S. Potter, G. Pringle, J. Slegers, C. Smith, D. Spooner, N. Thomas, J. Torero, S. Welch, W. J. Xue, S. J. Pennycook and all FireGrid team members not mentioned here.",
year = "2011",
month = jun,
doi = "10.1016/j.simpat.2011.01.007",
language = "English",
volume = "19",
pages = "1479--1495",
journal = "Simulation Modelling Practice and Theory",
issn = "1569-190X",
publisher = "Elsevier",
number = "6",

}

RIS

TY - JOUR

T1 - Managing dynamic enterprise and urgent workloads on clouds using layered queuing and historical performance models

AU - Bacigalupo, David A.

AU - Van Hemert, Jano

AU - Chen, Xiaoyu

AU - Usmani, Asif

AU - Chester, Adam P.

AU - He, Ligang

AU - Dillenberger, Donna N.

AU - Wills, Gary B.

AU - Gilbert, Lester

AU - Jarvis, Stephen A.

N1 - Funding Information: This work was sponsored in part by the JISC TeciRes project, the Technology Strategy Board FireGrid Project, The University of Edinburgh School of Informatics, the EPSRC DOPCHE Project (GR/S03058/01). We gratefully acknowledge the assistance during current and earlier versions of this work of: M. Atkinson, G. Beckett, J. Koetsier, S. Koo, T. Liu, I. Mitrani, A. van Moorsel, G. Nudd, S. Potter, G. Pringle, J. Slegers, C. Smith, D. Spooner, N. Thomas, J. Torero, S. Welch, W. J. Xue, S. J. Pennycook and all FireGrid team members not mentioned here.

PY - 2011/6

Y1 - 2011/6

N2 - The automatic allocation of enterprise workload to resources can be enhanced by being able to make what-if response time predictions whilst different allocations are being considered. We experimentally investigate an historical and a layered queuing performance model and show how they can provide a good level of support for a dynamic-urgent cloud environment. Using this we define, implement and experimentally investigate the effectiveness of a prediction-based cloud workload and resource management algorithm. Based on these experimental analyses we: (i) comparatively evaluate the layered queuing and historical techniques; (ii) evaluate the effectiveness of the management algorithm in different operating scenarios; and (iii) provide guidance on using prediction-based workload and resource management.

AB - The automatic allocation of enterprise workload to resources can be enhanced by being able to make what-if response time predictions whilst different allocations are being considered. We experimentally investigate an historical and a layered queuing performance model and show how they can provide a good level of support for a dynamic-urgent cloud environment. Using this we define, implement and experimentally investigate the effectiveness of a prediction-based cloud workload and resource management algorithm. Based on these experimental analyses we: (i) comparatively evaluate the layered queuing and historical techniques; (ii) evaluate the effectiveness of the management algorithm in different operating scenarios; and (iii) provide guidance on using prediction-based workload and resource management.

KW - Cloud

KW - FireGrid

KW - HYDRA historical model

KW - Layered queuing

KW - Performance modelling

UR - http://www.scopus.com/inward/record.url?scp=79955654404&partnerID=8YFLogxK

U2 - 10.1016/j.simpat.2011.01.007

DO - 10.1016/j.simpat.2011.01.007

M3 - Article

AN - SCOPUS:79955654404

VL - 19

SP - 1479

EP - 1495

JO - Simulation Modelling Practice and Theory

JF - Simulation Modelling Practice and Theory

SN - 1569-190X

IS - 6

ER -