A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf
.
Multiagent Reinforcement Learning for Task Offloading of Space/Aerial-Assisted Edge Computing
2022
Security and Communication Networks
The task offloading in space-aerial-ground integrated network (SAGIN) has been envisioned as a challenging issue. In this paper, we investigate a space/aerial-assisted edge computing network architecture considering whether to take advantage of edge server mounted on the unmanned aerial vehicle and satellite for task offloading or not. By optimizing the energy consumption and completion delay, we formulate a NP-hard and non-convex optimization problem to minimize the computation cost, limited
doi:10.1155/2022/4193365
fatcat:62vfmqsemzccbknvsparzvuwda