基于深度确定性策略梯度的星地融合网络可拆分任务卸载算法

Translated title of the contribution: Split task offloading algorithm for satellite-ground integrated networks based on deep deterministic policy gradient

Xiaoqin Song, Zhihao Wu, Haiguang Lai, Lei Lei, Lijuan Zhang, Danyang Lyu, Chenghui Zheng

Research output: Contribution to journalArticlepeer-review

Abstract

To address the prolonged task offloading delay in low earth orbit satellite networks, a split task offloading algorithm based on deep deterministic policy gradient (DDPG) was proposed for satellite-ground integrated networks. A multi-access edge computing structural model of the satellite-ground integrated network was established for users in different regions. By applying a multi-agent DDPG algorithm, the objective of minimizing total system service delay was transformed into maximizing agent reward returns. Under the constraints of sub-task offloading, service delay, and other task offloading conditions, the user task splitting ratio was optimized. Simulation results indicate that the proposed algorithm outperforms baseline algorithms in terms of user service delay and the number of benefited users.

Translated title of the contributionSplit task offloading algorithm for satellite-ground integrated networks based on deep deterministic policy gradient
Original languageChinese (Traditional)
Pages (from-to)116-128
Number of pages13
JournalTongxin Xuebao/Journal on Communications
Volume45
Issue number10
DOIs
Publication statusPublished - Oct 2024
Externally publishedYes

Fingerprint

Dive into the research topics of 'Split task offloading algorithm for satellite-ground integrated networks based on deep deterministic policy gradient'. Together they form a unique fingerprint.

Cite this