Quality of service evaluation of IaaS modeler allocation strategies on cloud computing simulator

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Cloud computing is becoming popular among application developers nowadays. With the advent of cloud, application developers can use computing resources that are cost effective with almost zero hardware maintenance worries. Many Simulators for Cloud platform has been developed to better understand the behavior of this platform and one of the commonly used simulator is CloudSim. The Cloud simulator (CloudSim) is a tool that provides an environment for investigating and understanding the federation of cloud entities and events. The effect of variation in parameters such as number of host, host MIPS, host RAM (MB) size, host storage, host bandwidth and VM and cloudlet completion time in IaaS modeler has been studied in this work. The scheduling policy for allocating processing cores to virtual machines has also been studied. We introduce an approach using PCA and clustering technique that is expected to perform better compared to the existing FCFS method for the allocation strategy.

Original languageEnglish
Title of host publicationProceedings of International Conference on High Performance Compilation, Computing and Communications, HP3C 2017
PublisherAssociation for Computing Machinery
Pages6-10
Number of pages5
VolumePart F128051
ISBN (Electronic)9781450348683
DOIs
Publication statusPublished - 22 Mar 2017
Event2017 International Conference on High Performance Compilation, Computing and Communications, HP3C 2017 - Kuala Lumpur, Malaysia
Duration: 22 Mar 201724 Mar 2017

Other

Other2017 International Conference on High Performance Compilation, Computing and Communications, HP3C 2017
CountryMalaysia
CityKuala Lumpur
Period22/3/1724/3/17

Fingerprint

Cloud computing
Quality of service
Simulators
Random access storage
Scheduling
Hardware
Bandwidth
Processing
Costs

Keywords

  • Cloud computing
  • Cloudlet.
  • Datacenter
  • Simulator
  • Virtual machine

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

Xue, L. S., Abd Majid, N. A., & A Sundararajan, E. (2017). Quality of service evaluation of IaaS modeler allocation strategies on cloud computing simulator. In Proceedings of International Conference on High Performance Compilation, Computing and Communications, HP3C 2017 (Vol. Part F128051, pp. 6-10). Association for Computing Machinery. https://doi.org/10.1145/3069593.3069607

Quality of service evaluation of IaaS modeler allocation strategies on cloud computing simulator. / Xue, Law Siew; Abd Majid, Nazatul Aini; A Sundararajan, Elankovan.

Proceedings of International Conference on High Performance Compilation, Computing and Communications, HP3C 2017. Vol. Part F128051 Association for Computing Machinery, 2017. p. 6-10.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Xue, LS, Abd Majid, NA & A Sundararajan, E 2017, Quality of service evaluation of IaaS modeler allocation strategies on cloud computing simulator. in Proceedings of International Conference on High Performance Compilation, Computing and Communications, HP3C 2017. vol. Part F128051, Association for Computing Machinery, pp. 6-10, 2017 International Conference on High Performance Compilation, Computing and Communications, HP3C 2017, Kuala Lumpur, Malaysia, 22/3/17. https://doi.org/10.1145/3069593.3069607
Xue LS, Abd Majid NA, A Sundararajan E. Quality of service evaluation of IaaS modeler allocation strategies on cloud computing simulator. In Proceedings of International Conference on High Performance Compilation, Computing and Communications, HP3C 2017. Vol. Part F128051. Association for Computing Machinery. 2017. p. 6-10 https://doi.org/10.1145/3069593.3069607
Xue, Law Siew ; Abd Majid, Nazatul Aini ; A Sundararajan, Elankovan. / Quality of service evaluation of IaaS modeler allocation strategies on cloud computing simulator. Proceedings of International Conference on High Performance Compilation, Computing and Communications, HP3C 2017. Vol. Part F128051 Association for Computing Machinery, 2017. pp. 6-10
@inproceedings{292a27feaefd497592b03f9aad75c56d,
title = "Quality of service evaluation of IaaS modeler allocation strategies on cloud computing simulator",
abstract = "Cloud computing is becoming popular among application developers nowadays. With the advent of cloud, application developers can use computing resources that are cost effective with almost zero hardware maintenance worries. Many Simulators for Cloud platform has been developed to better understand the behavior of this platform and one of the commonly used simulator is CloudSim. The Cloud simulator (CloudSim) is a tool that provides an environment for investigating and understanding the federation of cloud entities and events. The effect of variation in parameters such as number of host, host MIPS, host RAM (MB) size, host storage, host bandwidth and VM and cloudlet completion time in IaaS modeler has been studied in this work. The scheduling policy for allocating processing cores to virtual machines has also been studied. We introduce an approach using PCA and clustering technique that is expected to perform better compared to the existing FCFS method for the allocation strategy.",
keywords = "Cloud computing, Cloudlet., Datacenter, Simulator, Virtual machine",
author = "Xue, {Law Siew} and {Abd Majid}, {Nazatul Aini} and {A Sundararajan}, Elankovan",
year = "2017",
month = "3",
day = "22",
doi = "10.1145/3069593.3069607",
language = "English",
volume = "Part F128051",
pages = "6--10",
booktitle = "Proceedings of International Conference on High Performance Compilation, Computing and Communications, HP3C 2017",
publisher = "Association for Computing Machinery",

}

TY - GEN

T1 - Quality of service evaluation of IaaS modeler allocation strategies on cloud computing simulator

AU - Xue, Law Siew

AU - Abd Majid, Nazatul Aini

AU - A Sundararajan, Elankovan

PY - 2017/3/22

Y1 - 2017/3/22

N2 - Cloud computing is becoming popular among application developers nowadays. With the advent of cloud, application developers can use computing resources that are cost effective with almost zero hardware maintenance worries. Many Simulators for Cloud platform has been developed to better understand the behavior of this platform and one of the commonly used simulator is CloudSim. The Cloud simulator (CloudSim) is a tool that provides an environment for investigating and understanding the federation of cloud entities and events. The effect of variation in parameters such as number of host, host MIPS, host RAM (MB) size, host storage, host bandwidth and VM and cloudlet completion time in IaaS modeler has been studied in this work. The scheduling policy for allocating processing cores to virtual machines has also been studied. We introduce an approach using PCA and clustering technique that is expected to perform better compared to the existing FCFS method for the allocation strategy.

AB - Cloud computing is becoming popular among application developers nowadays. With the advent of cloud, application developers can use computing resources that are cost effective with almost zero hardware maintenance worries. Many Simulators for Cloud platform has been developed to better understand the behavior of this platform and one of the commonly used simulator is CloudSim. The Cloud simulator (CloudSim) is a tool that provides an environment for investigating and understanding the federation of cloud entities and events. The effect of variation in parameters such as number of host, host MIPS, host RAM (MB) size, host storage, host bandwidth and VM and cloudlet completion time in IaaS modeler has been studied in this work. The scheduling policy for allocating processing cores to virtual machines has also been studied. We introduce an approach using PCA and clustering technique that is expected to perform better compared to the existing FCFS method for the allocation strategy.

KW - Cloud computing

KW - Cloudlet.

KW - Datacenter

KW - Simulator

KW - Virtual machine

UR - http://www.scopus.com/inward/record.url?scp=85021436719&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85021436719&partnerID=8YFLogxK

U2 - 10.1145/3069593.3069607

DO - 10.1145/3069593.3069607

M3 - Conference contribution

VL - Part F128051

SP - 6

EP - 10

BT - Proceedings of International Conference on High Performance Compilation, Computing and Communications, HP3C 2017

PB - Association for Computing Machinery

ER -