Digital Twin-Based User-Centric Edge Continual Learning in Integrated Sensing and Communication

no code implementations • 20 Nov 2023 • Shisheng Hu, Jie Gao, Xinyu Huang, Mushu Li, Kaige Qu, Conghao Zhou, Xuemin, Shen

A DT of the ISAC device is constructed to predict the impact of potential decisions on the long-term computation cost of the server, based on which the decisions are made with closed-form formulas.

Continual Learning Edge-computing

Cost-Effective Two-Stage Network Slicing for Edge-Cloud Orchestrated Vehicular Networks

no code implementations • 31 Dec 2022 • Wen Wu, Kaige Qu, Peng Yang, Ning Zhang, Xuemin, Shen, Weihua Zhuang

Since the problem is NP-hard due to coupled network planning and network operation stages, we develop a Two timescAle netWork Slicing (TAWS) algorithm by collaboratively integrating reinforcement learning (RL) and optimization methods, which can jointly make network planning and operation decisions.

Reinforcement Learning (RL) Stochastic Optimization