Efficient virtual machine sizing for hosting containers as a service

Sareh Fotuhi Piraghaj; Amir Vahid Dastjerdi; Rodrigo N. Calheiros; Rajkumar Buyya

doi:10.1109/SERVICES.2015.14

Efficient virtual machine sizing for hosting containers as a service

Sareh Fotuhi Piraghaj, Amir Vahid Dastjerdi, Rodrigo N. Calheiros, Rajkumar Buyya

Western Sydney University

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

47 Citations (Scopus)

Abstract

There has been a growing effort in decreasing energy consumption of large-scale cloud data centers via maximization of host-level utilization and load balancing techniques. However, with the recent introduction of Container as a Service (CaaS) by cloud providers, maximizing the utilization at virtual machine (VM) level becomes essential. To this end, this paper focuses on finding efficient virtual machine sizes for hosting containers in such a way that the workload is executed with minimum wastage of resources on VM level. Suitable VM sizes for containers are calculated, and application tasks are grouped and clustered based on their usage patterns obtained from historical data. Furthermore, tasks are mapped to containers and containers are hosted on their associated VM types. We analyzed clouds' trace logs from Google cluster and consider the cloud workload variances, which is crucial for testing and validating our proposed solutions. Experimental results showed up to 7.55% improvement in the average energy consumption compared to baseline scenarios where the virtual machine sizes are fixed. In addition, comparing to the baseline scenarios, the total number of VMs instantiated for hosting the containers is also improved by 68% on average.

Original language	English
Title of host publication	Proceedings of the 2015 IEEE World Congress on Services: SERVICES 2015, 27 June - 2 July 2015, New York, New York, USA
Publisher	IEEE
Pages	31-38
Number of pages	8
ISBN (Print)	9781467372756
DOIs	https://doi.org/10.1109/SERVICES.2015.14
Publication status	Published - 2015
Event	IEEE World Congress on Services - Duration: 27 Jun 2015 → …

Conference

Conference	IEEE World Congress on Services
Period	27/06/15 → …

Keywords

cloud computing
data processing service centers
energy consumption

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10.1109/SERVICES.2015.14

Cite this

@inproceedings{11d77dc8c99e42b8a5bc1a1240b9db15,

title = "Efficient virtual machine sizing for hosting containers as a service",

abstract = "There has been a growing effort in decreasing energy consumption of large-scale cloud data centers via maximization of host-level utilization and load balancing techniques. However, with the recent introduction of Container as a Service (CaaS) by cloud providers, maximizing the utilization at virtual machine (VM) level becomes essential. To this end, this paper focuses on finding efficient virtual machine sizes for hosting containers in such a way that the workload is executed with minimum wastage of resources on VM level. Suitable VM sizes for containers are calculated, and application tasks are grouped and clustered based on their usage patterns obtained from historical data. Furthermore, tasks are mapped to containers and containers are hosted on their associated VM types. We analyzed clouds' trace logs from Google cluster and consider the cloud workload variances, which is crucial for testing and validating our proposed solutions. Experimental results showed up to 7.55% improvement in the average energy consumption compared to baseline scenarios where the virtual machine sizes are fixed. In addition, comparing to the baseline scenarios, the total number of VMs instantiated for hosting the containers is also improved by 68% on average.",

keywords = "cloud computing, data processing service centers, energy consumption",

author = "Piraghaj, {Sareh Fotuhi} and Dastjerdi, {Amir Vahid} and Calheiros, {Rodrigo N.} and Rajkumar Buyya",

year = "2015",

doi = "10.1109/SERVICES.2015.14",

language = "English",

isbn = "9781467372756",

pages = "31--38",

booktitle = "Proceedings of the 2015 IEEE World Congress on Services: SERVICES 2015, 27 June - 2 July 2015, New York, New York, USA",

publisher = "IEEE",

note = "IEEE World Congress on Services ; Conference date: 27-06-2015",

}

Efficient virtual machine sizing for hosting containers as a service. / Piraghaj, Sareh Fotuhi; Dastjerdi, Amir Vahid; Calheiros, Rodrigo N. et al.
Proceedings of the 2015 IEEE World Congress on Services: SERVICES 2015, 27 June - 2 July 2015, New York, New York, USA. IEEE, 2015. p. 31-38.

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

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AU - Dastjerdi, Amir Vahid

AU - Calheiros, Rodrigo N.

AU - Buyya, Rajkumar

PY - 2015

Y1 - 2015

N2 - There has been a growing effort in decreasing energy consumption of large-scale cloud data centers via maximization of host-level utilization and load balancing techniques. However, with the recent introduction of Container as a Service (CaaS) by cloud providers, maximizing the utilization at virtual machine (VM) level becomes essential. To this end, this paper focuses on finding efficient virtual machine sizes for hosting containers in such a way that the workload is executed with minimum wastage of resources on VM level. Suitable VM sizes for containers are calculated, and application tasks are grouped and clustered based on their usage patterns obtained from historical data. Furthermore, tasks are mapped to containers and containers are hosted on their associated VM types. We analyzed clouds' trace logs from Google cluster and consider the cloud workload variances, which is crucial for testing and validating our proposed solutions. Experimental results showed up to 7.55% improvement in the average energy consumption compared to baseline scenarios where the virtual machine sizes are fixed. In addition, comparing to the baseline scenarios, the total number of VMs instantiated for hosting the containers is also improved by 68% on average.

AB - There has been a growing effort in decreasing energy consumption of large-scale cloud data centers via maximization of host-level utilization and load balancing techniques. However, with the recent introduction of Container as a Service (CaaS) by cloud providers, maximizing the utilization at virtual machine (VM) level becomes essential. To this end, this paper focuses on finding efficient virtual machine sizes for hosting containers in such a way that the workload is executed with minimum wastage of resources on VM level. Suitable VM sizes for containers are calculated, and application tasks are grouped and clustered based on their usage patterns obtained from historical data. Furthermore, tasks are mapped to containers and containers are hosted on their associated VM types. We analyzed clouds' trace logs from Google cluster and consider the cloud workload variances, which is crucial for testing and validating our proposed solutions. Experimental results showed up to 7.55% improvement in the average energy consumption compared to baseline scenarios where the virtual machine sizes are fixed. In addition, comparing to the baseline scenarios, the total number of VMs instantiated for hosting the containers is also improved by 68% on average.

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KW - data processing service centers

KW - energy consumption

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ER -

Efficient virtual machine sizing for hosting containers as a service

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