跳到正文
研踪PaperTrail

YOUR RESEARCH, IN SIGHT

让下一篇重要论文,不再错过。

覆盖计算机全学科,以 AI 为快捷入口。关注方向、作者和关键词,把发现变成持续的研究积累。

部分采集异常
正在读取账号与研究记录…

全站更新概况

+1673新增论文
+1257其中 AI 相关
+198已有论文修订
+100新增 AI 导读

arXiv 最近完成扫描:2026-11-13 20:33 · 全站最近入库:2026-11-13 20:44各信源进度 →

统计口径与数据新鲜度

统计 2026-11-12 21:16 — 2026-11-13 21:16(北京时间) · 点击数字查看对应简报;AI 相关包含在新增论文内。

最近完成检查:2026-11-13 20:33最近发现新增版本:2026-11-13 20:44库内论文最新更新时间:2026-11-13 02:59

每分钟刷新已保存的数据。空检查不代表采集异常;新收录可能包含历史论文。AI 导读按新增版本计数。

23,348 已收录论文19,580 AI 相关6,727 有修订112 HF 社区发现

浏览论文库

时间范围跟随排序:版本更新、本站收录或首次发表。最新收录可能包含历史论文。部分信源异常,查看状态 →

找到 1 篇论文 · 按版本更新时间排序上轮扫描起点 2026-11-13 20:29(北京时间)
新论文 · v1arXiv:2611.13019

Two-Tier Task Offloading for Satellite-Assisted Marine Networks: A Hybrid Stackelberg-Bargaining Game Approach

Zhen Wang, Bin Lin, Qiang, Ye, Haixia Peng

原文摘要

The proliferation of maritime activities has spurred the emergence of numerous computation-intensive and delay-sensitive marine applications and services. Given the inherent rationality, selfish nature, and limited computational abilities of marine devices, devising effective strategies to incentivize their participation in task processing become a critical challenge. In this paper, we investigate the satellite-assisted marine multi-access edge computing (MEC) and propose a two-tier task offloading scheme through a hybrid Stackelberg-Bargaining game approach to enhance offloading efficiency and maximize the utility of marine devices. Specifically, for the underwater acoustic communication, we consider the scenario where multiple autonomous underwater vehicles (AUVs), managed by maritime autonomous surface ships (MASSs), upload their collected data using non-orthogonal multiple access(NOMA) to optimize channel utilization. For the data transmission above the sea surface, we consider the scenario where a low earth orbit satellite (LEOS) functions as a space edge server to provide computing services, and MASS offloads workloads to LEOS through frequency division multiple access(FDMA) to prevent co-channel interference. we define the utility of AUVs, MASSs and LEOSs, and model the offloading process between AUVs and MASSs as a Stackelberg game, while representing the offloading interaction between MASSs and LEOSs as a Bargaining game. Additionally, we propose efficient algorithms to optimize AUV offloading strategies and MASS pricing strategies, while refining the bidding strategies for both MASSs and LEOSs. Simulation results demonstrate that the proposed algorithms significantly outperform benchmark schemes in achieving optimal solutions.

cs.DC