6 papers
DistrEE: Distributed Early Exit of Deep Neural Network Inference on Edge Devices
Xian Peng, Xin Wu, Lianming Xu +2
Distributed DNN inference is becoming increasingly important as the demand for intelligent services at the network edge grows. By leveraging the power of distributed computing, edg…
Failure-Resilient Distributed Inference with Model Compression over Heterogeneous Edge Devices
Li Wang, Liang Li, Lianming Xu +2
The distributed inference paradigm enables the computation workload to be distributed across multiple devices, facilitating the implementations of deep learning based intelligent s…
Emergency Caching: Coded Caching-based Reliable Map Transmission in Emergency Networks
Zeyu Tian, Lianming Xu, Liang Li +2
Many rescue missions demand effective perception and real-time decision making, which highly rely on effective data collection and processing. In this study, we propose a three-lay…
Emergency Computing: An Adaptive Collaborative Inference Method Based on Hierarchical Reinforcement Learning
Weiqi Fu, Lianming Xu, Xin Wu +2
In achieving effective emergency response, the timely acquisition of environmental information, seamless command data transmission, and prompt decision-making are crucial. This nec…
An Improved Virtual Force Approach for UAV Deployment and Resource Allocation in Emergency Communications
Hongying Guo, Li Wang, Ruoguang Li +3
In this paper, we consider an unmanned aerial vehicle (UAV)-enabled emergency communication system, which establishes temporary communication link with users equipment (UEs) in a t…
Propagation Path Loss Models in Forest Scenario at 605 MHz
Zhe Xiao, Shu Sun, Zhenyu Liu +4
When signals propagate through forest areas, they will be affected by environmental factors such as vegetation. Different types of environments have different influences on signal…