Exploiting user provided information in dynamic consolidation of virtual machines to minimize energy consumption of cloud data centers

Md Anit Khan, Andrew P. Paplinski, Abdul Malik Khan, Manzur Murshed, Rajkumar Buyya

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

Dynamic consolidation of Virtual Machines (VMs) can effectively enhance the resource utilization and energy-efficiency of the Cloud Data Centers (CDC). Existing research on Cloud resource reservation and scheduling signify that Cloud Service Users (CSUs) can play a crucial role in improving the resource utilization by providing valuable information to Cloud service providers. However, utilization of CSUs' provided information in minimization of energy consumption of CDC is a novel research direction. The challenges herein are twofold. First, finding the right benign information to be received from a CSU which can complement the energy-efficiency of CDC. Second, smart application of such information to significantly reduce the energy consumption of CDC. To address those research challenges, we have proposed a novel heuristic Dynamic VM Consolidation algorithm, RTDVMC, which minimizes the energy consumption of CDC through exploiting CSU provided information. Our research exemplifies the fact that if VMs are dynamically consolidated based on the time when a VM can be removed from CDC-a useful information to be received from respective CSU, then more physical machines can be turned into sleep state, yielding lower energy consumption. We have simulated the performance of RTDVMC with real Cloud workload traces originated from more than 800 PlanetLab VMs. The empirical figures affirm the superiority of RTDVMC over existing prominent Static and Adaptive Threshold based DVMC algorithms.

Original languageEnglish
Title of host publication2018 Second International Conference on Fog and Mobile Edge Computing (FMEC)
Subtitle of host publication23-26 April, 2018 Barcelona, Spain
EditorsAndy Rindos, Chirine Ghedira, Danda Rawat
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages105-114
Number of pages10
ISBN (Electronic)9781538658963, 9781538658956
ISBN (Print)9781538658970
DOIs
Publication statusPublished - 2018
EventInternational Conference on Fog and Mobile Edge Computing 2018 - Barcelona, Spain
Duration: 23 Apr 201826 Apr 2018
Conference number: 2nd
http://emergingtechnet.org/FMEC2018/

Conference

ConferenceInternational Conference on Fog and Mobile Edge Computing 2018
Abbreviated titleFMEC 2018
CountrySpain
CityBarcelona
Period23/04/1826/04/18
Internet address

Keywords

  • Cloud Energy Efficiency
  • Cloud User Provided Information Aware
  • Dynamic VM Consolidation
  • Dynamic VM Placement
  • Energy-Efficient Cloud
  • Energy-Efficient Cloud Data Center
  • Green Cloud
  • Release Time based VM Consolidation
  • VM Consolidation
  • VM placement
  • Workload Consolidation

Cite this

Khan, M. A., Paplinski, A. P., Khan, A. M., Murshed, M., & Buyya, R. (2018). Exploiting user provided information in dynamic consolidation of virtual machines to minimize energy consumption of cloud data centers. In A. Rindos, C. Ghedira, & D. Rawat (Eds.), 2018 Second International Conference on Fog and Mobile Edge Computing (FMEC): 23-26 April, 2018 Barcelona, Spain (pp. 105-114). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/FMEC.2018.8364052
Khan, Md Anit ; Paplinski, Andrew P. ; Khan, Abdul Malik ; Murshed, Manzur ; Buyya, Rajkumar. / Exploiting user provided information in dynamic consolidation of virtual machines to minimize energy consumption of cloud data centers. 2018 Second International Conference on Fog and Mobile Edge Computing (FMEC): 23-26 April, 2018 Barcelona, Spain. editor / Andy Rindos ; Chirine Ghedira ; Danda Rawat. Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2018. pp. 105-114
@inproceedings{835afd1a4d6b4737a2a27e017c54b07d,
title = "Exploiting user provided information in dynamic consolidation of virtual machines to minimize energy consumption of cloud data centers",
abstract = "Dynamic consolidation of Virtual Machines (VMs) can effectively enhance the resource utilization and energy-efficiency of the Cloud Data Centers (CDC). Existing research on Cloud resource reservation and scheduling signify that Cloud Service Users (CSUs) can play a crucial role in improving the resource utilization by providing valuable information to Cloud service providers. However, utilization of CSUs' provided information in minimization of energy consumption of CDC is a novel research direction. The challenges herein are twofold. First, finding the right benign information to be received from a CSU which can complement the energy-efficiency of CDC. Second, smart application of such information to significantly reduce the energy consumption of CDC. To address those research challenges, we have proposed a novel heuristic Dynamic VM Consolidation algorithm, RTDVMC, which minimizes the energy consumption of CDC through exploiting CSU provided information. Our research exemplifies the fact that if VMs are dynamically consolidated based on the time when a VM can be removed from CDC-a useful information to be received from respective CSU, then more physical machines can be turned into sleep state, yielding lower energy consumption. We have simulated the performance of RTDVMC with real Cloud workload traces originated from more than 800 PlanetLab VMs. The empirical figures affirm the superiority of RTDVMC over existing prominent Static and Adaptive Threshold based DVMC algorithms.",
keywords = "Cloud Energy Efficiency, Cloud User Provided Information Aware, Dynamic VM Consolidation, Dynamic VM Placement, Energy-Efficient Cloud, Energy-Efficient Cloud Data Center, Green Cloud, Release Time based VM Consolidation, VM Consolidation, VM placement, Workload Consolidation",
author = "Khan, {Md Anit} and Paplinski, {Andrew P.} and Khan, {Abdul Malik} and Manzur Murshed and Rajkumar Buyya",
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Khan, MA, Paplinski, AP, Khan, AM, Murshed, M & Buyya, R 2018, Exploiting user provided information in dynamic consolidation of virtual machines to minimize energy consumption of cloud data centers. in A Rindos, C Ghedira & D Rawat (eds), 2018 Second International Conference on Fog and Mobile Edge Computing (FMEC): 23-26 April, 2018 Barcelona, Spain. IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, pp. 105-114, International Conference on Fog and Mobile Edge Computing 2018, Barcelona, Spain, 23/04/18. https://doi.org/10.1109/FMEC.2018.8364052

Exploiting user provided information in dynamic consolidation of virtual machines to minimize energy consumption of cloud data centers. / Khan, Md Anit; Paplinski, Andrew P.; Khan, Abdul Malik; Murshed, Manzur; Buyya, Rajkumar.

2018 Second International Conference on Fog and Mobile Edge Computing (FMEC): 23-26 April, 2018 Barcelona, Spain. ed. / Andy Rindos; Chirine Ghedira; Danda Rawat. Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2018. p. 105-114.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

TY - GEN

T1 - Exploiting user provided information in dynamic consolidation of virtual machines to minimize energy consumption of cloud data centers

AU - Khan, Md Anit

AU - Paplinski, Andrew P.

AU - Khan, Abdul Malik

AU - Murshed, Manzur

AU - Buyya, Rajkumar

PY - 2018

Y1 - 2018

N2 - Dynamic consolidation of Virtual Machines (VMs) can effectively enhance the resource utilization and energy-efficiency of the Cloud Data Centers (CDC). Existing research on Cloud resource reservation and scheduling signify that Cloud Service Users (CSUs) can play a crucial role in improving the resource utilization by providing valuable information to Cloud service providers. However, utilization of CSUs' provided information in minimization of energy consumption of CDC is a novel research direction. The challenges herein are twofold. First, finding the right benign information to be received from a CSU which can complement the energy-efficiency of CDC. Second, smart application of such information to significantly reduce the energy consumption of CDC. To address those research challenges, we have proposed a novel heuristic Dynamic VM Consolidation algorithm, RTDVMC, which minimizes the energy consumption of CDC through exploiting CSU provided information. Our research exemplifies the fact that if VMs are dynamically consolidated based on the time when a VM can be removed from CDC-a useful information to be received from respective CSU, then more physical machines can be turned into sleep state, yielding lower energy consumption. We have simulated the performance of RTDVMC with real Cloud workload traces originated from more than 800 PlanetLab VMs. The empirical figures affirm the superiority of RTDVMC over existing prominent Static and Adaptive Threshold based DVMC algorithms.

AB - Dynamic consolidation of Virtual Machines (VMs) can effectively enhance the resource utilization and energy-efficiency of the Cloud Data Centers (CDC). Existing research on Cloud resource reservation and scheduling signify that Cloud Service Users (CSUs) can play a crucial role in improving the resource utilization by providing valuable information to Cloud service providers. However, utilization of CSUs' provided information in minimization of energy consumption of CDC is a novel research direction. The challenges herein are twofold. First, finding the right benign information to be received from a CSU which can complement the energy-efficiency of CDC. Second, smart application of such information to significantly reduce the energy consumption of CDC. To address those research challenges, we have proposed a novel heuristic Dynamic VM Consolidation algorithm, RTDVMC, which minimizes the energy consumption of CDC through exploiting CSU provided information. Our research exemplifies the fact that if VMs are dynamically consolidated based on the time when a VM can be removed from CDC-a useful information to be received from respective CSU, then more physical machines can be turned into sleep state, yielding lower energy consumption. We have simulated the performance of RTDVMC with real Cloud workload traces originated from more than 800 PlanetLab VMs. The empirical figures affirm the superiority of RTDVMC over existing prominent Static and Adaptive Threshold based DVMC algorithms.

KW - Cloud Energy Efficiency

KW - Cloud User Provided Information Aware

KW - Dynamic VM Consolidation

KW - Dynamic VM Placement

KW - Energy-Efficient Cloud

KW - Energy-Efficient Cloud Data Center

KW - Green Cloud

KW - Release Time based VM Consolidation

KW - VM Consolidation

KW - VM placement

KW - Workload Consolidation

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U2 - 10.1109/FMEC.2018.8364052

DO - 10.1109/FMEC.2018.8364052

M3 - Conference Paper

SN - 9781538658970

SP - 105

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BT - 2018 Second International Conference on Fog and Mobile Edge Computing (FMEC)

A2 - Rindos, Andy

A2 - Ghedira, Chirine

A2 - Rawat, Danda

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Piscataway NJ USA

ER -

Khan MA, Paplinski AP, Khan AM, Murshed M, Buyya R. Exploiting user provided information in dynamic consolidation of virtual machines to minimize energy consumption of cloud data centers. In Rindos A, Ghedira C, Rawat D, editors, 2018 Second International Conference on Fog and Mobile Edge Computing (FMEC): 23-26 April, 2018 Barcelona, Spain. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. 2018. p. 105-114 https://doi.org/10.1109/FMEC.2018.8364052