11 citations · 16 across the 7 of their papers we have counts for
7 papers
Spatiotemporal Non-Uniformity-Aware Online Task Scheduling in Collaborative Edge Computing for Industrial Internet of Things
Yang Li, Xing Zhang, Yukun Sun +2
Mobile edge computing mitigates the shortcomings of cloud computing caused by unpredictable wide-area network latency and serves as a critical enabling technology for the Industria…
Incentive-Driven Task Offloading and Collaborative Computing in Device-Assisted MEC Networks
Yang Li, Xing Zhang, Bo Lei +4
Edge computing (EC), positioned near end devices, holds significant potential for delivering low-latency, energy-efficient, and secure services. This makes it a crucial component o…
Adaptive Multi-Layer Deployment for A Digital Twin Empowered Satellite-Terrestrial Integrated Network
Yihong Tao, Bo Lei, Haoyang Shi +2
With the development of satellite communication technology, satellite-terrestrial integrated networks (STIN), which integrate satellite networks and ground networks, can realize se…
Priority and Stackelberg Game-Based Incentive Task Allocation for Device-Assisted MEC Networks
Yang Li, Xing Zhang, Bo Lei +2
Mobile edge computing (MEC) is a promising computing paradigm that offers users proximity and instant computing services for various applications, and it has become an essential co…
Computation Rate Maximization for Wireless Powered Edge Computing With Multi-User Cooperation
Yang Li, Xing Zhang, Bo Lei +4
The combination of mobile edge computing (MEC) and radio frequency-based wireless power transfer (WPT) presents a promising technique for providing sustainable energy supply and co…
Joint Task Partitioning and Parallel Scheduling in Device-Assisted Mobile Edge Networks
Yang Li, Xinlei Ge, Bo Lei +2
With the development of the Internet of Things (IoT), certain IoT devices have the capability to not only accomplish their own tasks but also simultaneously assist other resource-c…
Communication Efficiency Optimization of Federated Learning for Computing and Network Convergence of 6G Networks
Yizhuo Cai, Bo Lei, Qianying Zhao +4
Federated learning effectively addresses issues such as data privacy by collaborating across participating devices to train global models. However, factors such as network topology…