Partial Computation Offloading in Satellite-Based Three-Tier Cloud-Edge Integration Networks

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Abstract
Computation offloading tends to be an effective way for mitigating computing pressure of user equipments (UEs). By computation offloading, the task can be handled in network edge and/or cloud center to compensate insufficient resources and capabilities of UEs. In this study, we construct a three-tier cloud-edge integration network, where user tasks are offloaded to satellite based edge server and further to the remote ground cloud server via backhaul links. The optimization problem is modeled for minimizing system energy consumption and considers user association, power allocation, task scheduling, and bandwidth assignment jointly. By the proposed schemes based on relaxation transformation and fractional programming, four subproblems are transformed into corresponding convex optimization problems and solved respectively. In order to find the global optimal solutions, a joint iterative algorithm for three-tier computation offloading problem is designed. In numerical simulations, we compare different communication schemes and computation offloading schemes to present the rationality and superiority of the designed algorithm for reducing system energy consumption.
Funding Information
  • National Key Research and Development Program of China (2020YFB1806103)
  • National Natural Science Foundation of China (62225103, U22B2003)
  • Beijing Natural Science Foundation (L212004)
  • Xiaomi Fund of Young Scholar
  • China University Industry-University-Research Collaborative Innovation Fund (2021FNA05001)

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