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A Joint Optimization Scheme in Heterogeneous UAV-Assisted MEC

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Algorithms and Architectures for Parallel Processing (ICA3PP 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14490))

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Abstract

Mobile Edge Computing (MEC) is considered as a promising technology to meet the high-quality service requirements of emerging applications in mobile intelligent terminals. It can effectively handle computation-intensive and latency-sensitive tasks in the Internet of Things (IoT). However, location-fixed edge servers in MEC cannot efficiently handle time-varying tasks in the hot-spot area. Therefore, it is necessary to utilize the Unmanned Aerial Vehicle (UAV) with communication and computation resources making on-demand network deployment for handling the time-varying tasks above. In this paper, we build a novel MEC system based on heterogeneous multi-UAV, in which we take both the UAV scheduling problem and the task allocation problem into consideration. What’s more, in order to minimize the system energy consumption, we propose a joint optimization method, named JoSA, for the two problems mentioned above. To be specific, we first regard the UAV scheduling problem as a knapsack problem. Based on this, we then divide the tasks in the hot-spot area according to geographic location and allocate them in different situations. Finally, compared with the other two benchmarks, the simulation experiments show that our method demonstrates good generalization ability and makes better performance with a reduction of 8% and 11% in system energy consumption, and 3% and 4% in system time cost, respectively.

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Acknowledgments

This work was supported by the National Key Research and Development Program of China under Grant 2021ZD0112400, the National Natural Science Foundation of China under grant 62202080, the Science and Technology Project of Liaoning Province under grant 2021JH1/10400009, the CCF-Tencent Open Fund under grant IAGR20220114, the Liaoning Revitalization Talents Program under grant XLYC2008017, the Fundamental Research Funds for the Central Universities under grant DUT20RC(3)039.

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Authors and Affiliations

  1. School of Computer Science and Technology, Dalian University of Technology, Dalian, 116024, China

    Tian Qin, Pengfei Wang & Qiang Zhang

Authors
  1. Tian Qin
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  2. Pengfei Wang
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  3. Qiang Zhang
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Corresponding authors

Correspondence to Pengfei Wang or Qiang Zhang .

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Editors and Affiliations

  1. Royal Melbourne Institute of Technology, Melbourne, VIC, Australia

    Zahir Tari

  2. Tianjin University, Tianjin, China

    Keqiu Li

  3. University of Arizona, Tucson, AZ, USA

    Hongyi Wu

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Qin, T., Wang, P., Zhang, Q. (2024). A Joint Optimization Scheme in Heterogeneous UAV-Assisted MEC. In: Tari, Z., Li, K., Wu, H. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2023. Lecture Notes in Computer Science, vol 14490. Springer, Singapore. https://doi.org/10.1007/978-981-97-0859-8_12

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  • DOI: https://doi.org/10.1007/978-981-97-0859-8_12

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  • Print ISBN: 978-981-97-0858-1

  • Online ISBN: 978-981-97-0859-8

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