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Joint Offloading and Resource Allocation Based on UAV-Assisted Mobile Edge Computing

Published: 18 April 2022 Publication History

Abstract

Due to the birth of various new Internet of Things devices, the rapid increase of users, and the limited coverage of infrastructure, computing resources will inevitably become insufficient. Therefore, we consider an unmanned aerial vehicle (UAV)–assisted mobile edge computing system with multiple users, an edge server, a remote cloud server, and an UAV. A UAV, as a relay node, can provide users with extensive communications and certain computing capabilities. Our proposed scheme aims to optimize the unloading decision of the tasks among all users and the allocation of computing and communication resources to minimize overall energy consumption and costs of computing and maximum delay. To solve the joint optimization problem, we propose an efficient USS algorithm, which includes a UAV position optimization algorithm, semi-qualitative relaxation method, and self-adaptive adjustment method. Our numerical results show that the proposed algorithm can significantly reduce the unloading cost of multi-user tasks compared with four other unloading decisions, such as traditional cloud computing, which uses only the edge server.

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      Published In

      cover image ACM Transactions on Sensor Networks
      ACM Transactions on Sensor Networks  Volume 18, Issue 3
      August 2022
      480 pages
      ISSN:1550-4859
      EISSN:1550-4867
      DOI:10.1145/3531537
      Issue’s Table of Contents

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      Association for Computing Machinery

      New York, NY, United States

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      Publication History

      Published: 18 April 2022
      Online AM: 09 March 2022
      Accepted: 01 July 2021
      Revised: 01 June 2021
      Received: 01 March 2021
      Published in TOSN Volume 18, Issue 3

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      Author Tags

      1. Mobile edge computing
      2. unmanned aerial vehicle (UAV)
      3. unloading decision
      4. joint optimization problem
      5. USS algorithm

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      • Research-article
      • Refereed

      Funding Sources

      • Natural Science Foundation of Hunan Province, China

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      • (2024)SIM-OFE: Structure Information Mining and Object-Aware Feature Enhancement for Fine-Grained Visual CategorizationIEEE Transactions on Image Processing10.1109/TIP.2024.345978833(5312-5326)Online publication date: 1-Jan-2024
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