Mort: A Dependent Task Offloading Framework Towards Real-Time Data Distribution and Transmission Optimization

Yin Yuyu; Gou Hongshen; Li Youhuizi; Huang Binbin; Wan Jian

doi:10.7544/issn1000-1239.202220729

Journal of Computer Research and Development > 2023 > 60(5): 1002-1020. > DOI: 10.7544/issn1000-1239.202220729

Yin Yuyu, Gou Hongshen, Li Youhuizi, Huang Binbin, Wan Jian. Mort: A Dependent Task Offloading Framework Towards Real-Time Data Distribution and Transmission Optimization[J]. Journal of Computer Research and Development, 2023, 60(5): 1002-1020. DOI: 10.7544/issn1000-1239.202220729

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Mort: A Dependent Task Offloading Framework Towards Real-Time Data Distribution and Transmission Optimization

College of Computer Science & Technology, Hangzhou Dianzi University, Hangzhou 310018

Funds: This work was supported by Zhejiang Provincial Natural Science Foundation of China (LY22F020018) and the National Natural Science Foundation of China (62272140)

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Author Bio:
Yin Yuyu: born in 1980. PhD, professor. Member of CCF. His main research interests include service computing, edge computing, and business process management

Gou Hongshen: born in 1996. Master. His main research interests include service computing, edge computing and workflow scheduling

Li Youhuizi: born in 1989. PhD, associate professor. Member of CCF. Her main research interests include edge computing, privacy security, mobile edge computing, and energy efficiency system

Huang Binbin: born in 1984. PhD, associate professor. Her main research interests include cloud computing, mobile edge computing and workflow scheduling

Wan Jian: born in 1969. PhD, professor. His main research interests include distributed systems, computer networks, and big data analytics
Received Date: August 19, 2022
Revised Date: March 29, 2023
Available Online: April 09, 2023

Graphical Abstract

Abstract

Abstract

In edge collaborative computing, a single device can no longer support more and more complicated applications and services. Their tasks are offloaded to the adjacent edge server with rich computing and storage resources to match the various high calculation capabilities and low latency requirements. At the same time, the publish-subscribe system is commonly applied from the communication perspective to build a unified transmission protocol to protect data privacy. In the publish-subscribe system, tasks often execute periodicity, depend on each other and the data is distributed to different clients in high-frequency. However, the traditional task offloading algorithms mainly aim at the single data transmission and single task execution scenario, which cannot effectively handle the offloading characteristics in a publish-subscribe system. Therefore, we propose Mort, a task offloading and management framework. It supports task decomposition using the static program analysis technique, and the task dependencies are extracted and the parallelism is increased. Nonlinear integer programming-based modeling and group-based resource fusion-based offloading algorithms are applied to optimize network data transmission. The coordination process-based scheduling model is used to schedule the offloading tasks with less overhead. Our comprehensive experiments show that Mort’s data transmission optimization can reach 80%-90% of the optimal solution with a low overhead of only 2%.
- edge computing,
- publish-subscribe system,
- dependent task offloading,
- combination optimization,
- time-sensitive

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References (45)

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