most citedDistributed Optimization for Energy-efficient Fog Computing in the Tactile Internet

123 citations · 321 across the 5 of their papers we have counts for

collaborators

7 papers

eess.SP202035 cited

Towards Ubiquitous AI in 6G with Federated Learning

Yong Xiao, Guangming Shi, Marwan Krunz

With 5G cellular systems being actively deployed worldwide, the research community has started to explore novel technological advances for the subsequent generation, i.e., 6G. It i…

eess.SP2020

A Generative Learning Approach for Spatio-temporal Modeling in Connected Vehicular Network

Rong Xia, Yong Xiao, Yingyu Li +2

Spatio-temporal modeling of wireless access latency is of great importance for connected-vehicular systems. The quality of the molded results rely heavily on the number and quality…

cs.NI202079 cited

Dynamic Network Slicing for Scalable Fog Computing Systems with Energy Harvesting

Yong Xiao, Marwan Krunz

This paper studies fog computing systems, in which cloud data centers can be supplemented by a large number of fog nodes deployed in a wide geographical area. Each node relies on h…

cs.NI202049 cited

Distributed Resource Allocation for Network Slicing over Licensed and Unlicensed Bands

Yong Xiao, Mohammed Hirzallah, Marwan Krunz

Network slicing is considered one of the key enabling technologies for 5G due to its ability to customize and "slice" a common resource to support diverse services and verticals.Th…

cs.NI2020123 cited

Distributed Optimization for Energy-efficient Fog Computing in the Tactile Internet

Yong Xiao, Marwan Krunz

Tactile Internet is an emerging concept that focuses on supporting high-fidelity, ultra-responsive, and widely available human-to-machine interactions. To reduce the transmission l…

cs.NI202035 cited

Multi-operator Network Sharing for Massive IoT

Yong Xiao, Marwan Krunz, Tao Shu

Recent study predicts that by 2020 up to 50 billion IoT devices will be connected to the Internet, straining the capacity of wireless network that has already been overloaded with…