IET Communications (Mar 2023)

Joint UAV deployment, SF placement, and collaborative task scheduling in heterogeneous multi‐UAV‐empowered edge intelligence

  • Yangang Wang,
  • Xianglin Wei,
  • Hai Wang,
  • Jianhua Fan,
  • Juan Chen,
  • Kuang Zhao,
  • Yongyang Hu

DOI
https://doi.org/10.1049/cmu2.12570
Journal volume & issue
Vol. 17, no. 5
pp. 641 – 657

Abstract

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Abstract To support artificial intelligence (AI)‐involved tasks offloaded from the mobile devices (MDs), it is necessary to equip the Unmanned Aerial Vehicle (UAV) with custom‐made co‐processor (CP) for handling AI workloads in multi‐UAV‐empowered Edge Intelligence. Existing CPU‐oriented task scheduling algorithm cannot apply to the CPU+CP heterogeneous architecture. In this backdrop, this paper first formulates the joint service function placement, collaborative task scheduling, UAV deployment, and MD position determination problem as a Mixed Integer Non‐Linear Programming problem. Then, an alternating optimization‐based algorithm is put forward to derive a sub‐optimal solution of the problem utilizing Differential Evolution and Greedy‐based Hungarian algorithms. A series of experiments are conducted to evaluate the performance of the proposal. Results show that authors' proposal can achieve an overall revenue that is roughly 50% higher than those of existing methods.

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