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Efficient Dependent Task Offloading for Multiple Applications in MEC-Cloud System

Authors :
Yongmin Zhang
Jiagang Liu
Yaoxue Zhang
Yuanyuan Yang
Peng Xuhong
Ju Ren
Source :
IEEE Transactions on Mobile Computing. 22:2147-2162
Publication Year :
2023
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2023.

Abstract

With the proliferation of versatile mobile applications, offloading compute-intensive tasks to the MEC/Cloud becomes a dramatic technique due to the limited resources and high user experience requirements at mobile devices. However, most existing works design their task offloading schemes without considering the dependence of tasks and the orchestration of the MEC and Cloud, and thus may limit the system performance. In this paper, we propose a dependent task offloading framework for multiple mobile applications, named COFE, where mobile devices can offload their compute-intensive tasks with dependent constraints to the MEC-Cloud system. It can assign the offloaded tasks to the MEC and Cloud adaptively to improve the user experience. Based on COFE, we formulate the task offloading problem as an average makespan minimization problem, which is proved to be NP-hard. Then, we propose a heuristic ranking-based algorithm to assign the offloaded tasks according to their bottom levels. Theoretical analysis proves the stability of the system under the proposed algorithm and extensive simulations validate that the proposed algorithm can significantly reduce the average makespan and deadline violation probabilities of offloaded applications.

Details

ISSN :
21619875 and 15361233
Volume :
22
Database :
OpenAIRE
Journal :
IEEE Transactions on Mobile Computing
Accession number :
edsair.doi...........6f9325768dff291f5c902109b34fabd9
Full Text :
https://doi.org/10.1109/tmc.2021.3119200