Flow-Time Minimization for Timely Data Stream Processing in UAV-Aided Mobile Edge Computing
Authors: 
Zichuan Xu, Haiyang Qiao, Weifa Liang, Zhou Xu, Qiufen Xia, Pan Zhou, Omer F. Rana, Wenzheng XuAuthors Info & Claims
Zichuan Xu, Haiyang Qiao, Weifa Liang, Zhou Xu, Qiufen Xia, Pan Zhou, Omer F. Rana, Wenzheng XuAuthors Info & ClaimsArticle No.: 58, Pages 1 - 28
Abstract
Unmanned Aerial Vehicles (UAVs) have gained increasing attention by both academic and industrial communities, due to their flexible deployment and efficient line-of-sight communication. Recently, UAVs equipped with base stations have been envisioned as a key technology to provide 5G network services for mobile users. In this article, we provide timely services on the data streams of mobile users in a UAV-aided Mobile Edge Computing (MEC) network, in which each UAV is equipped with a 5G small-cell base station for communication and data processing. Specifically, we first formulate a flow-time minimization problem by jointly caching services and offloading tasks of mobile users to the UAV-aided MEC with the aim to minimize the flow time, where the flow time of a user request is referred to the time duration from the request issuing time point to its completion point, subject to resource and energy capacity on each UAV. We then propose a spatial-temporal learning optimization framework. We also devise an online algorithm with a competitive ratio for the problem based upon the framework, by leveraging the round-robin scheduling and dual fitting techniques. Finally, we evaluate the performance of the proposed algorithms through experimental simulation. The simulation results demonstrate that the proposed algorithms outperform their comparison counterparts, by reducing the flow time no less than 19% on average.
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Index Terms
- Flow-Time Minimization for Timely Data Stream Processing in UAV-Aided Mobile Edge Computing
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Publication History
Published: 13 March 2024
Online AM: 02 February 2024
Accepted: 11 January 2024
Revised: 17 November 2023
Received: 26 December 2022
Published in TOSN Volume 20, Issue 3
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- Shandong Provincial Natural Science Foundation
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