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author:

Wu, W. (Wu, W..) [1] | Feng, W. (Feng, W..) [2] | Fang, Y. (Fang, Y..) [3] | Lin, Z. (Lin, Z..) [4] | Lu, X. (Lu, X..) [5]

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Scopus

Abstract:

The growth of maritime activities has boosted the demand for efficient marine communications and computation offloading. Mobile edge computing (MEC)-powered space-air-ground-sea integrated network (SAGSIN) is a promising solution to satisfy these demands. To the best of our knowledge, the existing research on high altitude platforms (HAPs) in SAGSIN remains open. To exploit the HAPs' advantages of facilitating communication at shorter distances and more stable computing services than terrestrial base stations, this work considers multi-HAP-assisted computation offloading in SAGSIN and formulates an optimization problem, which turns out to be a mixed integer nonlinear programming (MINLP) due to the joint optimization among task-HAP association, computational resource allocation of HAPs and task-satellite association. To this end, the problem is decoupled into three single-variable subproblems by relaxing the delay constraint, and the subproblems are solved by graph theory, the Lagrange multiplier method with Karush-Kuhn-Tucker (KKT) constraints, and the alternating optimization, respectively. Simulation results demonstrate the efficiency of the proposed scheme with superior performances compared to benchmark schemes. © 2025 IEEE.

Keyword:

computation offloading high altitude platform (HAP) mobile edge computing (MEC) Space-air-ground-sea integrated network (SAGSIN)

Community:

  • [ 1 ] [Wu W.]Fuzhou University, School of Physics and Information Engineering, Fuzhou, 350108, China
  • [ 2 ] [Feng W.]Tsinghua University, Beijing National Research Center for Information Science and Technology, Department of Electronic Engineering, Beijing, 100084, China
  • [ 3 ] [Fang Y.]Guangdong University of Technology, School of Information Engineering, Guangzhou, 510006, China
  • [ 4 ] [Lin Z.]Fuzhou University, School of Physics and Information Engineering, Fuzhou, 350108, China
  • [ 5 ] [Lu X.]Fuzhou University, School of Physics and Information Engineering, Fuzhou, 350108, China

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Source :

IEEE Internet of Things Journal

ISSN: 2327-4662

Year: 2025

8 . 2 0 0

JCR@2023

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ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 1

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