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20242026
most citedCollaborative Satellite Computing through Adaptive DNN Task Splitting and Offloading

10 citations · 12 across the 10 of their papers we have counts for

collaborators

11 papers

cs.DC2026

A RAG-Enhanced Bi-Level Cognitive Orchestration Framework for LEO Satellite Networks

Yuhong Jiang, Zhishu Shen, Tong Yin +4

The rapid growth of remote sensing data in Low Earth Orbit (LEO) satellite networks is increasingly constrained by limited downlink capacity to terrestrial networks. Satellite edge…

cs.DC2025

A Semi-Supervised Federated Learning Framework with Hierarchical Clustering Aggregation for Heterogeneous Satellite Networks

Zhuocheng Liu, Zhishu Shen, Qiushi Zheng +3

Low Earth Orbit (LEO) satellites are emerging as key components of 6G networks, with many already deployed to support large-scale Earth observation and sensing related tasks. Feder…

cs.DC2025★ 1 cited

Intelligent Task Management via Dynamic Multi-region Division in LEO Satellite Networks

Zixuan Song, Zhishu Shen, Xiaoyu Zheng +3

As a key complement to terrestrial networks and a fundamental component of future 6G systems, Low Earth Orbit (LEO) satellite networks are expected to provide high-quality communic…

cs.CV2025

Farm-LightSeek: An Edge-centric Multimodal Agricultural IoT Data Analytics Framework with Lightweight LLMs

Dawen Jiang, Zhishu Shen, Qiushi Zheng +3

Amid the challenges posed by global population growth and climate change, traditional agricultural Internet of Things (IoT) systems is currently undergoing a significant digital tr…

cs.DC2025

CCRSat: A Collaborative Computation Reuse Framework for Satellite Edge Computing Networks

Ye Zhang, Zhishu Shen, Dawen Jiang +3

In satellite computing applications, such as remote sensing, tasks often involve similar or identical input data, leading to the same processing results. Computation reuse is an em…

cs.DC2025★ 1 cited

FedHC: A Hierarchical Clustered Federated Learning Framework for Satellite Networks

Zhuocheng Liu, Zhishu Shen, Pan Zhou +2

With the proliferation of data-driven services, the volume of data that needs to be processed by satellite networks has significantly increased. Federated learning (FL) is well-sui…

cs.DC2024

Collaborative UAVs Multi-task Video Processing Optimization Based on Enhanced Distributed Actor-Critic Networks

Ziqi Rong, Qiushi Zheng, Zhishu Shen +4

With the rapid advancement of the Internet of Things (IoT) and Artificial Intelligence (AI), intelligent information services are being increasingly integrated across various secto…

cs.CR2024

A Sharded Blockchain-Based Secure Federated Learning Framework for LEO Satellite Networks

Wenbo Wu, Cheng Tan, Kangcheng Yang +3

Low Earth Orbit (LEO) satellite networks are increasingly essential for space-based artificial intelligence (AI) applications. However, as commercial use expands, LEO satellite net…

cs.DC2024

Unleashing Collaborative Computing for Adaptive Video Streaming with Multi-objective Optimization in Satellite Terrestrial Networks

Zhishu Shen, Qiushi Zheng, Ziqi Rong +3

Satellite-terrestrial networks (STNs) are anticipated to deliver seamless IoT services across expansive regions. Given the constrained resources available for offloading computatio…

cs.DC2024★ 10 cited

Collaborative Satellite Computing through Adaptive DNN Task Splitting and Offloading

Shifeng Peng, Xuefeng Hou, Zhishu Shen +4

Satellite computing has emerged as a promising technology for next-generation wireless networks. This innovative technology provides data processing capabilities, which facilitates…

cs.DC2024

Lion: Minimizing Distributed Transactions through Adaptive Replica Provision (Extended Version)

Qiushi Zheng, Zhanhao Zhao, Wei Lu +4

Distributed transaction processing often involves multiple rounds of cross-node communications, and therefore tends to be slow. To improve performance, existing approaches convert…