9 papers · 1 filter
Jointly Optimizing Memory, Computing and Offloading for Energy-Efficient DNN Inference
Yunchu Han, Zhaojun Nan, Sheng Zhou +1
In edge intelligence systems, computation offloading and dynamic voltage and frequency scaling (DVFS) are widely used to improve energy efficiency. However, as applications like de…
FedPGT: Progressive Gradient Transmission for Vehicular Federated Learning over Time-Varying Channels
Jintao Yan, Tan Chen, Yuxuan Sun +2
Vehicular federated learning (VFL) enables privacy-preserving collaborative model training for intelligent transportation systems, where communication resource allocation and gradi…
Sylvas: Synergistic Learning Value based Device Scheduling in Federated Continual Learning
Yuxuan Sun, Yuxuan Bai, Tan Chen +2
Federated continual learning (FCL) enables shared global models to continuously adapt to distributed and non-stationary data streams, making it important for Internet of Things app…
Joint Optimization of Memory and Computing Frequency for Energy-Efficient DNN Inference
Yunchu Han, Zhaojun Nan, Sheng Zhou +1
Deep neural network (DNN) inference on mobile devices often incurs high latency and energy consumption due to limited computing and memory resources. To enable energy-efficient DNN…
DH-VLM: Dual-Horizon Cooperative Latent Reasoning for Autonomous Driving
Ziyi Song, Chen Xia, Hang Yu +2
Large-scale language models for autonomous driving enable enhanced global understanding and long-horizon planning. However, when deployed in isolated vehicles, limited sensing rang…
GeoFovea-GS: Geometry-Aware Cross-Layer Gaussian Splatting for Wireless Aerial VR
Zeyi Ren, Wencheng Yan, Jiawen Zhang +3
Wireless aerial virtual reality (VR) aims to provide immersive access to large-scale scenes, but high-resolution view generation and delivery are jointly constrained by limited ban…
TGPP: Trajectory-Guided Plug-and-Play Priors for Sparse Radio Map Reconstruction
Jiawen Zhang, Zhiyuan Jiang, Sheng Zhou +1
Radio map (RM) reconstruction is essential for environment-aware wireless networks, but practical measurements are often collected along mobility trajectories rather than randomly…
DiP-SD: Distributed Pipelined Speculative Decoding for Efficient LLM Inference at the Edge
Yaodan Xu, Sheng Zhou, Zhisheng Niu
Speculative decoding has emerged as a promising technique for large language model (LLM) inference by accelerating autoregressive decoding via draft-then-verify. This paper studies…
Efficient Transceiver Design for Aerial Image Transmission and Large-scale Scene Reconstruction
Zeyi Ren, Jialin Dong, Wei Zuo +4
Large-scale three-dimensional (3D) scene reconstruction in low-altitude intelligent networks (LAIN) demands highly efficient wireless image transmission. However, existing schemes…