Economic Impact of Resource Optimisation in Cloud Environment Using Different Virtual Machine Allocation Policies

Bilal Ahmad; Zaib Maroof; Sally McClean; Darryl Charles; Gerard Parr

doi:10.1007/978-3-030-23943-5_4

Economic Impact of Resource Optimisation in Cloud Environment Using Different Virtual Machine Allocation Policies

Bilal Ahmad, Zaib Maroof, Sally McClean, Darryl Charles, Gerard Parr

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

Abstract

Exceptional level of research work has been carried in the field of cloud and distributed systems for understanding their performance and reliability. Simulators are becoming popular for designing and testing different types of quality of service (QoS) matrices e.g. energy, virtualisation, and networking. A large amount of resource is wasted when servers are sitting idle which puts a negative impact on the financial aspects of companies. A popular approach used to overcome this problem is turning them ON/OFF. However, it takes time when they are turned ON affecting different matrices of QoS like energy consumption, latency, consumption and cost. In this paper, we present different energy models and their comparison with each other based on workloads for efficient server management. We introduce a different type of energy saving techniques (DVFs, IQRMC) which help toward an improvement in service. Different energy models are used with the same configuration and possible solutions are proposed for big data centres that are placed globally by large companies like Amazon, Giaki, Onlive, and Google.

Original language	English
Title of host publication	Emerging Technologies in Computing - 2nd International Conference, iCETiC 2019, Proceedings
Editors	Mahdi H. Miraz, Maaruf Ali, Safeeullah Soomro, Andrew Ware, Peter S. Excell
Publisher	Springer-Verlag Berlin Heidelberg
Pages	46-58
Number of pages	13
ISBN (Print)	9783030239428
DOIs	https://doi.org/10.1007/978-3-030-23943-5_4
Publication status	Published - 2019
Event	2nd International Conference on Emerging Technologies in Computing, iCETiC 2019 - London, United Kingdom Duration: 19 Aug 2019 → 20 Aug 2019

Publication series

Name	Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume	285
ISSN (Print)	1867-8211

Conference

Conference	2nd International Conference on Emerging Technologies in Computing, iCETiC 2019
Country/Territory	United Kingdom
City	London
Period	19/08/19 → 20/08/19

Keywords

Cloud computing
Economic impact
Energy optimisation
Green computing
Resource optimisation
Service quality
Virtualisation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-23943-5_4

Cite this

Ahmad, B., Maroof, Z., McClean, S., Charles, D., & Parr, G. (2019). Economic Impact of Resource Optimisation in Cloud Environment Using Different Virtual Machine Allocation Policies. In M. H. Miraz, M. Ali, S. Soomro, A. Ware, & P. S. Excell (Eds.), Emerging Technologies in Computing - 2nd International Conference, iCETiC 2019, Proceedings (pp. 46-58). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 285). Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-030-23943-5_4

Ahmad, Bilal ; Maroof, Zaib ; McClean, Sally et al. / Economic Impact of Resource Optimisation in Cloud Environment Using Different Virtual Machine Allocation Policies. Emerging Technologies in Computing - 2nd International Conference, iCETiC 2019, Proceedings. editor / Mahdi H. Miraz ; Maaruf Ali ; Safeeullah Soomro ; Andrew Ware ; Peter S. Excell. Springer-Verlag Berlin Heidelberg, 2019. pp. 46-58 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST).

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Ahmad, B, Maroof, Z, McClean, S, Charles, D & Parr, G 2019, Economic Impact of Resource Optimisation in Cloud Environment Using Different Virtual Machine Allocation Policies. in MH Miraz, M Ali, S Soomro, A Ware & PS Excell (eds), Emerging Technologies in Computing - 2nd International Conference, iCETiC 2019, Proceedings. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 285, Springer-Verlag Berlin Heidelberg, pp. 46-58, 2nd International Conference on Emerging Technologies in Computing, iCETiC 2019, London, United Kingdom, 19/08/19. https://doi.org/10.1007/978-3-030-23943-5_4

Economic Impact of Resource Optimisation in Cloud Environment Using Different Virtual Machine Allocation Policies. / Ahmad, Bilal; Maroof, Zaib; McClean, Sally et al.

Emerging Technologies in Computing - 2nd International Conference, iCETiC 2019, Proceedings. ed. / Mahdi H. Miraz; Maaruf Ali; Safeeullah Soomro; Andrew Ware; Peter S. Excell. Springer-Verlag Berlin Heidelberg, 2019. p. 46-58 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 285).

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

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T1 - Economic Impact of Resource Optimisation in Cloud Environment Using Different Virtual Machine Allocation Policies

AU - Ahmad, Bilal

AU - Maroof, Zaib

AU - McClean, Sally

AU - Charles, Darryl

AU - Parr, Gerard

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N2 - Exceptional level of research work has been carried in the field of cloud and distributed systems for understanding their performance and reliability. Simulators are becoming popular for designing and testing different types of quality of service (QoS) matrices e.g. energy, virtualisation, and networking. A large amount of resource is wasted when servers are sitting idle which puts a negative impact on the financial aspects of companies. A popular approach used to overcome this problem is turning them ON/OFF. However, it takes time when they are turned ON affecting different matrices of QoS like energy consumption, latency, consumption and cost. In this paper, we present different energy models and their comparison with each other based on workloads for efficient server management. We introduce a different type of energy saving techniques (DVFs, IQRMC) which help toward an improvement in service. Different energy models are used with the same configuration and possible solutions are proposed for big data centres that are placed globally by large companies like Amazon, Giaki, Onlive, and Google.

AB - Exceptional level of research work has been carried in the field of cloud and distributed systems for understanding their performance and reliability. Simulators are becoming popular for designing and testing different types of quality of service (QoS) matrices e.g. energy, virtualisation, and networking. A large amount of resource is wasted when servers are sitting idle which puts a negative impact on the financial aspects of companies. A popular approach used to overcome this problem is turning them ON/OFF. However, it takes time when they are turned ON affecting different matrices of QoS like energy consumption, latency, consumption and cost. In this paper, we present different energy models and their comparison with each other based on workloads for efficient server management. We introduce a different type of energy saving techniques (DVFs, IQRMC) which help toward an improvement in service. Different energy models are used with the same configuration and possible solutions are proposed for big data centres that are placed globally by large companies like Amazon, Giaki, Onlive, and Google.

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KW - Economic impact

KW - Energy optimisation

KW - Green computing

KW - Resource optimisation

KW - Service quality

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AN - SCOPUS:85070651949

SN - 9783030239428

T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

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BT - Emerging Technologies in Computing - 2nd International Conference, iCETiC 2019, Proceedings

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A2 - Ali, Maaruf

A2 - Soomro, Safeeullah

A2 - Ware, Andrew

A2 - Excell, Peter S.

PB - Springer-Verlag Berlin Heidelberg

T2 - 2nd International Conference on Emerging Technologies in Computing, iCETiC 2019

Y2 - 19 August 2019 through 20 August 2019

ER -

Ahmad B, Maroof Z, McClean S, Charles D, Parr G. Economic Impact of Resource Optimisation in Cloud Environment Using Different Virtual Machine Allocation Policies. In Miraz MH, Ali M, Soomro S, Ware A, Excell PS, editors, Emerging Technologies in Computing - 2nd International Conference, iCETiC 2019, Proceedings. Springer-Verlag Berlin Heidelberg. 2019. p. 46-58. (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST). Epub 2019 Jul 14. doi: 10.1007/978-3-030-23943-5_4

Economic Impact of Resource Optimisation in Cloud Environment Using Different Virtual Machine Allocation Policies

Abstract

Publication series

Conference

Keywords

UN SDGs

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Gerard Parr

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