6 papers
Cross-Problem Solving for Network Optimization: Is Problem-Aware Learning the Key?
Ruihuai Liang, Bo Yang, Pengyu Chen +4
As intelligent network services continue to diversify, ensuring efficient and adaptive resource allocation in edge networks has become increasingly critical. Yet the wide functiona…
Frontiers of Generative AI for Network Optimization: Theories, Limits, and Visions
Bo Yang, Ruihuai Liang, Weixin Li +8
While interest in the application of generative AI (GenAI) in network optimization has surged in recent years, its rapid progress has often overshadowed critical limitations intrin…
Joint Task Offloading and Resource Allocation in Low-Altitude MEC via Graph Attention Diffusion
Yifan Xue, Ruihuai Liang, Bo Yang +4
With the rapid development of the low-altitude economy, air-ground integrated multi-access edge computing (MEC) systems are facing increasing demands for real-time and intelligent…
GDSG: Graph Diffusion-based Solution Generator for Optimization Problems in MEC Networks
Ruihuai Liang, Bo Yang, Pengyu Chen +6
Optimization is crucial for MEC networks to function efficiently and reliably, most of which are NP-hard and lack efficient approximation algorithms. This leads to a paucity of opt…
DiffSG: A Generative Solver for Network Optimization with Diffusion Model
Ruihuai Liang, Bo Yang, Zhiwen Yu +5
Generative diffusion models, famous for their performance in image generation, are popular in various cross-domain applications. However, their use in the communication community h…
Diffusion Models as Network Optimizers: Explorations and Analysis
Ruihuai Liang, Bo Yang, Pengyu Chen +8
Network optimization is a fundamental challenge in the Internet of Things (IoT) network, often characterized by complex features that make it difficult to solve these problems. Rec…