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Volume 44 Issue 9
Sep.  2022
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LI Bin, LIU Wenshuai, FEI Zesong. Partial Computation Offloading for Mobile Edge Computing in Space-Air-Ground Integrated Network[J]. Journal of Electronics & Information Technology, 2022, 44(9): 3091-3098. doi: 10.11999/JEIT220272
Citation: LI Bin, LIU Wenshuai, FEI Zesong. Partial Computation Offloading for Mobile Edge Computing in Space-Air-Ground Integrated Network[J]. Journal of Electronics & Information Technology, 2022, 44(9): 3091-3098. doi: 10.11999/JEIT220272

Partial Computation Offloading for Mobile Edge Computing in Space-Air-Ground Integrated Network

doi: 10.11999/JEIT220272
Funds:  The National Key R&D Program of China (2020YFB1806900), The National Natural Science Foundation of China (62101277), The Science Foundation of Jiangsu Province (BK20200822), The Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX22_1204)
  • Received Date: 2022-03-14
  • Rev Recd Date: 2022-05-28
  • Available Online: 2022-06-14
  • Publish Date: 2022-09-19
  • As a new type of network architecture, Space-Air-Ground Integrated Network (SAGIN) is the key support for 6G to realize ubiquitous connection in the future. In this paper, a partial task offloading approach for Mobile Edge Computing (MEC) in SAGIN is proposed. Firstly, the coverage time of Low Earth Orbit (LEO) satellite is analyzed. Then, a non-convex and multivariable coupling problem for minimization of total energy consumption of all Unmanned Aerial Vehicles (UAVs) is formulated by the joint design of the association control, computation task allocation, bandwidth allocation, UAV computation resource, and UAV trajectory. To solve this problem, the alternation optimization technique is invoked to decouple the original non-convex problem into three subproblems which are solved by the successive convex approximation method. Numerical results demonstrate that the proposed algorithm has good convergence performance and reduces effectively the system energy consumption.
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