DATA: Dependency-Aware Task Allocation Scheme in Distributed Edge Clouds

Jaewook Lee; Haneul Ko; Joonwoo Kim; Sangheon Pack

doi:10.1109/TII.2020.2990674

DATA: Dependency-Aware Task Allocation Scheme in Distributed Edge Clouds

Jaewook Lee, Haneul Ko, Joonwoo Kim, Sangheon Pack

Research output: Contribution to journal › Article › peer-review

41 Citations (Scopus)

Abstract

To overcome the limitation of standalone edge cloud in terms of computing power and resource, a concept of distributed edge cloud has been introduced, where application tasks are distributed to multiple edge clouds for collaborative processing. To maximize the effectiveness of the distributed edge cloud, we formulate an optimization problem of task allocation to minimize the application completion time. To mitigate high complexity overhead in the formulated problem, we devise a low-complexity heuristic algorithm called dependency-aware task allocation (DATA) algorithm. Evaluation results demonstrate that DATA can reduce the application completion time up to by 15%-32% compared to conventional dependency-unaware task allocation schemes.

Original language	English
Article number	9079591
Pages (from-to)	7782-7790
Number of pages	9
Journal	IEEE Transactions on Industrial Informatics
Volume	16
Issue number	12
DOIs	https://doi.org/10.1109/TII.2020.2990674
Publication status	Published - 2020 Dec

Bibliographical note

Funding Information:
This work was supported in part by the National Research Foundation of Korea Grant funded by the Korean Government (MSIP) under Grant 2020R1A2C3006786 and in part by the Samsung Research in Samsung Electronics. Paper no. TII-19-4415.

Funding Information:
Manuscript received September 28, 2019; revised January 5, 2020; accepted April 15, 2020. Date of publication April 27, 2020; date of current version September 18, 2020. This work was supported in part by the National Research Foundation of Korea Grant funded by the Korean Government (MSIP) under Grant 2020R1A2C3006786 and in part by the Samsung Research in Samsung Electronics. Paper no. TII-19-4415. (Corresponding author: Sangheon Pack.) Jaewook Lee, Joonwoo Kim, and Sangheon Pack are with the School of Electrical Engineering, Korea University, Seoul 02841, South Korea (e-mail: [email protected]; [email protected]; [email protected]).

Publisher Copyright:
© 2005-2012 IEEE.

Keywords

Distributed edge cloud
heuristic algorithm
mixed integer nonlinear program (MINLP)
optimization

ASJC Scopus subject areas

Control and Systems Engineering
Information Systems
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/TII.2020.2990674

Cite this

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abstract = "To overcome the limitation of standalone edge cloud in terms of computing power and resource, a concept of distributed edge cloud has been introduced, where application tasks are distributed to multiple edge clouds for collaborative processing. To maximize the effectiveness of the distributed edge cloud, we formulate an optimization problem of task allocation to minimize the application completion time. To mitigate high complexity overhead in the formulated problem, we devise a low-complexity heuristic algorithm called dependency-aware task allocation (DATA) algorithm. Evaluation results demonstrate that DATA can reduce the application completion time up to by 15\%-32\% compared to conventional dependency-unaware task allocation schemes.",

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DATA: Dependency-Aware Task Allocation Scheme in Distributed Edge Clouds

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Keywords

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