Numerical and simulation verification for optimal server allocation in edge computing

Dawei Li; Chigozie Asikaburu; Jiacheng Shang; Ning Wang

doi:10.1109/IEMTRONICS52119.2021.9422538

Numerical and simulation verification for optimal server allocation in edge computing

Dawei Li, Chigozie Asikaburu, Jiacheng Shang, Ning Wang

Computer Science

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

1 Scopus citations

Abstract

In this paper, we consider the server allocation problem in edge computing. We consider a system model where there are a number of areas or locations, each of which has an associated Base Station (BS), where we can deploy an edge cloud with multiple servers. Each edge cloud will process application requests received at the corresponding BS from users in the corresponding area. The system manager/operator has a budget to deploy a given number of servers to the BSs. Our goal is to come up with a server allocation plan, i.e., how many servers to deploy at each of the BSs, such that the overall average turnaround time of application requests generated by all the users is minimized. In order to achieve the optimal solution for the problem, we resort to queueing theory and model each edge cloud as an M/M/c queue. Analysis on the problem motivates a Largest Weighted Reduction Time First (LWRTF) algorithm to assign servers to edge clouds. Numerical comparisons among various algorithms verify that Algorithm LWRTF has near-optimal performances in terms of minimizing the average turnaround time. Simulation results using the CloudSim Plus simulation tool also verify that Algorithm LWRTF achieves better performances compared to other reasonably designed heuristic algorithms.

Original language	English
Title of host publication	2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 - Proceedings
Editors	Satyajit Chakrabarti, Rajashree Paul, Bob Gill, Malay Gangopadhyay, Sanghamitra Poddar
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665440677
DOIs	https://doi.org/10.1109/IEMTRONICS52119.2021.9422538
State	Published - 21 Apr 2021
Event	2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 - Toronto, Canada Duration: 21 Apr 2021 → 24 Apr 2021

Publication series

Name	2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 - Proceedings

Conference

Conference	2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021
Country/Territory	Canada
City	Toronto
Period	21/04/21 → 24/04/21

Keywords

Edge cloud
Edge computing
Numerical method
Queueing theory
Simulation approach

Access to Document

10.1109/IEMTRONICS52119.2021.9422538

Cite this

Li, D., Asikaburu, C., Shang, J., & Wang, N. (2021). Numerical and simulation verification for optimal server allocation in edge computing. In S. Chakrabarti, R. Paul, B. Gill, M. Gangopadhyay, & S. Poddar (Eds.), 2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 - Proceedings Article 9422538 (2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IEMTRONICS52119.2021.9422538

Li, Dawei ; Asikaburu, Chigozie ; Shang, Jiacheng et al. / Numerical and simulation verification for optimal server allocation in edge computing. 2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 - Proceedings. editor / Satyajit Chakrabarti ; Rajashree Paul ; Bob Gill ; Malay Gangopadhyay ; Sanghamitra Poddar. Institute of Electrical and Electronics Engineers Inc., 2021. (2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 - Proceedings).

@inproceedings{6bdaca59e02c4546834760fec9efa6df,

title = "Numerical and simulation verification for optimal server allocation in edge computing",

abstract = "In this paper, we consider the server allocation problem in edge computing. We consider a system model where there are a number of areas or locations, each of which has an associated Base Station (BS), where we can deploy an edge cloud with multiple servers. Each edge cloud will process application requests received at the corresponding BS from users in the corresponding area. The system manager/operator has a budget to deploy a given number of servers to the BSs. Our goal is to come up with a server allocation plan, i.e., how many servers to deploy at each of the BSs, such that the overall average turnaround time of application requests generated by all the users is minimized. In order to achieve the optimal solution for the problem, we resort to queueing theory and model each edge cloud as an M/M/c queue. Analysis on the problem motivates a Largest Weighted Reduction Time First (LWRTF) algorithm to assign servers to edge clouds. Numerical comparisons among various algorithms verify that Algorithm LWRTF has near-optimal performances in terms of minimizing the average turnaround time. Simulation results using the CloudSim Plus simulation tool also verify that Algorithm LWRTF achieves better performances compared to other reasonably designed heuristic algorithms.",

keywords = "Edge cloud, Edge computing, Numerical method, Queueing theory, Simulation approach",

author = "Dawei Li and Chigozie Asikaburu and Jiacheng Shang and Ning Wang",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 ; Conference date: 21-04-2021 Through 24-04-2021",

year = "2021",

month = apr,

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doi = "10.1109/IEMTRONICS52119.2021.9422538",

language = "English",

series = "2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

editor = "Satyajit Chakrabarti and Rajashree Paul and Bob Gill and Malay Gangopadhyay and Sanghamitra Poddar",

booktitle = "2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 - Proceedings",

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Li, D, Asikaburu, C, Shang, J & Wang, N 2021, Numerical and simulation verification for optimal server allocation in edge computing. in S Chakrabarti, R Paul, B Gill, M Gangopadhyay & S Poddar (eds), 2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 - Proceedings., 9422538, 2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021, Toronto, Canada, 21/04/21. https://doi.org/10.1109/IEMTRONICS52119.2021.9422538

Numerical and simulation verification for optimal server allocation in edge computing. / Li, Dawei; Asikaburu, Chigozie; Shang, Jiacheng et al.
2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 - Proceedings. ed. / Satyajit Chakrabarti; Rajashree Paul; Bob Gill; Malay Gangopadhyay; Sanghamitra Poddar. Institute of Electrical and Electronics Engineers Inc., 2021. 9422538 (2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 - Proceedings).

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

TY - GEN

T1 - Numerical and simulation verification for optimal server allocation in edge computing

AU - Li, Dawei

AU - Asikaburu, Chigozie

AU - Shang, Jiacheng

AU - Wang, Ning

PY - 2021/4/21

Y1 - 2021/4/21

N2 - In this paper, we consider the server allocation problem in edge computing. We consider a system model where there are a number of areas or locations, each of which has an associated Base Station (BS), where we can deploy an edge cloud with multiple servers. Each edge cloud will process application requests received at the corresponding BS from users in the corresponding area. The system manager/operator has a budget to deploy a given number of servers to the BSs. Our goal is to come up with a server allocation plan, i.e., how many servers to deploy at each of the BSs, such that the overall average turnaround time of application requests generated by all the users is minimized. In order to achieve the optimal solution for the problem, we resort to queueing theory and model each edge cloud as an M/M/c queue. Analysis on the problem motivates a Largest Weighted Reduction Time First (LWRTF) algorithm to assign servers to edge clouds. Numerical comparisons among various algorithms verify that Algorithm LWRTF has near-optimal performances in terms of minimizing the average turnaround time. Simulation results using the CloudSim Plus simulation tool also verify that Algorithm LWRTF achieves better performances compared to other reasonably designed heuristic algorithms.

AB - In this paper, we consider the server allocation problem in edge computing. We consider a system model where there are a number of areas or locations, each of which has an associated Base Station (BS), where we can deploy an edge cloud with multiple servers. Each edge cloud will process application requests received at the corresponding BS from users in the corresponding area. The system manager/operator has a budget to deploy a given number of servers to the BSs. Our goal is to come up with a server allocation plan, i.e., how many servers to deploy at each of the BSs, such that the overall average turnaround time of application requests generated by all the users is minimized. In order to achieve the optimal solution for the problem, we resort to queueing theory and model each edge cloud as an M/M/c queue. Analysis on the problem motivates a Largest Weighted Reduction Time First (LWRTF) algorithm to assign servers to edge clouds. Numerical comparisons among various algorithms verify that Algorithm LWRTF has near-optimal performances in terms of minimizing the average turnaround time. Simulation results using the CloudSim Plus simulation tool also verify that Algorithm LWRTF achieves better performances compared to other reasonably designed heuristic algorithms.

KW - Edge cloud

KW - Edge computing

KW - Numerical method

KW - Queueing theory

KW - Simulation approach

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U2 - 10.1109/IEMTRONICS52119.2021.9422538

DO - 10.1109/IEMTRONICS52119.2021.9422538

M3 - Conference contribution

AN - SCOPUS:85106719520

T3 - 2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 - Proceedings

BT - 2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 - Proceedings

A2 - Chakrabarti, Satyajit

A2 - Paul, Rajashree

A2 - Gill, Bob

A2 - Gangopadhyay, Malay

A2 - Poddar, Sanghamitra

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021

Y2 - 21 April 2021 through 24 April 2021

ER -

Li D, Asikaburu C, Shang J, Wang N. Numerical and simulation verification for optimal server allocation in edge computing. In Chakrabarti S, Paul R, Gill B, Gangopadhyay M, Poddar S, editors, 2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2021. 9422538. (2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 - Proceedings). doi: 10.1109/IEMTRONICS52119.2021.9422538

Numerical and simulation verification for optimal server allocation in edge computing

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