8 citations · 15 across the 6 of their papers we have counts for
7 papers
Spectrum-aware Multi-hop Task Routing in Vehicle-assisted Collaborative Edge Computing
Yiqin Deng, Haixia Zhang, Xianhao Chen +1
Multi-access edge computing (MEC) is a promising technology to enhance the quality of service, particularly for low-latency services, by enabling computing offloading to edge serve…
Vehicle as a Service (VaaS): Leverage Vehicles to Build Service Networks and Capabilities for Smart Cities
Xianhao Chen, Yiqin Deng, Haichuan Ding +4
Smart cities demand resources for rich immersive sensing, ubiquitous communications, powerful computing, large storage, and high intelligence (SCCSI) to support various kinds of ap…
Communication and Energy Efficient Wireless Federated Learning with Intrinsic Privacy
Zhenxiao Zhang, Yuanxiong Guo, Yuguang Fang +1
Federated Learning (FL) is a collaborative learning framework that enables edge devices to collaboratively learn a global model while keeping raw data locally. Although FL avoids l…
Efficient Parallel Split Learning over Resource-constrained Wireless Edge Networks
Zheng Lin, Guangyu Zhu, Yiqin Deng +4
The increasingly deeper neural networks hinder the democratization of privacy-enhancing distributed learning, such as federated learning (FL), to resource-constrained devices. To o…
Cooperative Beamforming Design for Multiple RIS-Assisted Communication Systems
Xiaoyan Ma, Yuguang Fang, Haixia Zhang +2
Reconfigurable intelligent surface (RIS) provides a promising way to build programmable wireless transmission environments. Owing to the massive number of controllable reflecting e…
Actions at the Edge: Jointly Optimizing the Resources in Multi-access Edge Computing
Yiqin Deng, Xianhao Chen, Guangyu Zhu +3
Multi-access edge computing (MEC) is an emerging paradigm that pushes resources for sensing, communications, computing, storage and intelligence (SCCSI) to the premises closer to t…